Information retrieval Books

Book SynopsisThis witty book helps you understand how data compression algorithms work-in theory and practice-so you can choose the best solution among all the available compression tools.

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Book SynopsisThis book covers semiconductor memory technologies from device bit-cell structures to memory array design with an emphasis on recent industry scaling trends and cutting-edge technologies. The first part of the book discusses the mainstream semiconductor memory technologies. The second part of the book discusses the emerging memory candidates that may have the potential to change the memory hierarchy, and surveys new applications of memory technologies for machine/deep learning applications. This book is intended for graduate students in electrical and computer engineering programs and researchers or industry professionals in semiconductors and microelectronics. Explains the design of basic memory bit-cells including 6-transistor SRAM, 1-transistor-1-capacitor DRAM, and floating gate/charge trap FLASH transistor Examines the design of the peripheral circuits including the sense amplifier and array-level organization for the memory array Examines industry trends of memory technologies such as FinFET based SRAM, High-Bandwidth-Memory (HBM), 3D NAND Flash, and 3D X-point array Discusses the prospects and challenges of emerging memory technologies such as PCM, RRAM, STT-MRAM/SOT-MRAM and FeRAM/FeFET Explores the new applications such as in-memory computing for AI hardware acceleration.

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Book SynopsisAmateur astronomers are always on the lookout for new observing challenges. This is a practical guide to locating and viewing the most impressive of Herschel’s star clusters, nebulae and galaxies, cataloging more than 600 of the brightest objects, and offering detailed descriptions and images of 150 to 200 of the best.Trade ReviewFrom the reviews: "Mullaney packs an incredible amount of information into this 166-page book. … All in all, The Herschel Objects, and how to observe them is engaging, challenging, well-written, and comprehensive. So, if you love deep-sky observing – and even if you’ve observed the Astronomical League’s Herschel 400 – Mullaney’s book offers a new list with several hundred additional objects you’ll enjoy." (Michael Bakich, Astronomy Magazine, October, 2007) "The Herschel Objects and How to Observe Them is a fine addition to the Springer series of observing guides. Mullaney has been observing the Herschel objects for many years and his passion for them clearly comes across. … Overall though, this is a book that will be a useful addition to any deep-sky observer’s library." (Paul Money, BBC Sky at Night, February, 2008) "Mullaney begins with a well-written biographical sketch of Herschel and his family, and explains the significance of the work of this great observational astronomer. … the objects are illustrated with excellent images obtained using a modern charge-coupled device (CCD) system. The book concludes with a list of 618 targets that would provide for a lifetime of study. The book will be of greatest interest to experienced observers who wish to push on to the most challenging deep sky objects. … Summing Up: Recommended. General readers." (D. E. Hogg, CHOICE, Vol. 45 (6), February, 2008) "The book opens with a few short chapters on Herschel himself together with a brief introduction to observing techniques … . rounded out with some objects that the author regards as showpieces that were not discovered by Herschel. Any collection of these will of course be very subjective. … I found the book’s reproductions to be a cut above the usual Springer ones and the book does offers something sufficiently different … and the Astronomical League guides to make it worth adding to your collection." (Owen Brazell, The Observatory, Vol. 128 (1203), 2008)Table of ContentsWilliam Herschel's Life, Telescopes and Catalogs.- Herschel's Telescopes.- Herschel's Catalogs and Classes.- Observing Techniques.- Exploring The Herschel Showpieces.- Showpieces of Class I.- Showpieces of Class IV.- Showpieces of Class V.- Showpieces of Class VI.- Showpieces of Class VII.- Showpieces of Class VIII.- Samples of Classes II & III.- Showpieces Missed by Herschel.- The “Missing” Herschel Objects.- Conclusion.

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Book SynopsisClass-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book''s supporting website to help course instructors prepare their lectures.Trade Review'This is the first book that gives you a complete picture of the complications that arise in building a modern web-scale search engine. You'll learn about ranking SVMs, XML, DNS, and LSI. You'll discover the seedy underworld of spam, cloaking, and doorway pages. You'll see how MapReduce and other approaches to parallelism allow us to go beyond megabytes and to efficiently manage petabytes.' Peter Norvig, Director of Research, Google Inc.'… this book sets a high standard …' Natural Language Engineering'Introduction to Information Retrieval is a comprehensive, authoritative, and well-written overview of the main topics in IR. The book offers a good balance of theory and practice, and is an excellent self-contained introductory text for those new to IR.' Computational Linguistics'This book provides what Salton and Van Rijsbergen both failed to achieve … Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. … its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.' Natural Language EngineeringTable of Contents1. Information retrieval using the Boolean model; 2. The dictionary and postings lists; 3. Tolerant retrieval; 4. Index construction; 5. Index compression; 6. Scoring and term weighting; 7. Vector space retrieval; 8. Evaluation in information retrieval; 9. Relevance feedback and query expansion; 10. XML retrieval; 11. Probabilistic information retrieval; 12. Language models for information retrieval; 13. Text classification and Naive Bayes; 14. Vector space classification; 15. Support vector machines and kernel functions; 16. Flat clustering; 17. Hierarchical clustering; 18. Dimensionality reduction and latent semantic indexing; 19. Web search basics; 20. Web crawling and indexes; 21. Link analysis.

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Book SynopsisSearch is among the most disruptive innovations of our time. It influences what we buy and where we go. It shapes how we learn and what we believe. This book explores design patterns that apply across the categories of web, ecommerce, enterprise, desktop, mobile, social, and realtime search and discovery.

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Book SynopsisData manipulation and analysis are easier than you might imagine. Using tools that come standard with your desktop computer, you can learn how to extract, manipulate, and analyse data of any size and complexity. This book familiarizes readers with easily digestible but powerful concepts that will enable you to feel confident working with data.Trade ReviewI highly recommend The Data Wrangler’s Handbook for anyone who now manipulates data or may need to do so in the future. In Banerjee’s words, 'If these tasks [that require data wrangling] sound intimidating, this book is for you. You will understand everything in this book even if you have no special technical knowledge or programming experience.'"" — TechnicalitiesTable of Contents List of Figures and Tables Acknowledgments Introduction Chapter 1 Getting Started with the Command Line Finding the Command Line Mac Windows Meet the Command Line Chapter 2 Command Line Concepts Two Powerful Symbols Direct Output to a File (Greater Than Symbol) Direct Output to Another Program (Pipe Symbol) Command Substitution Regular Expressions—The Swiss Army Knife for Data Literal Characters Special Characters Wildcard Characters Logical Operators Grouping Scripting Chapter 3 Understanding Formats, by David Forero Chapter 4 Simplify Complicated Problems Isolating Specific Data Elements Converting Data into Formats That Are Easier to Work With Chapter 5 Delimited Text CSV (Comma Separated Values) Commas and Quotation Marks in CSV Files Multiline Fields in CSV Files Multivalued Fields in Delimited Files Chapter 6 XML So What Is XML, Really? What Makes XML So Useful? Why Is XML So Easy? DOM (Document Object Model) XPath XSLT (eXtensible Stylesheet Language Transformations) Working with Large XML Files Working with Complex XML Files XmlStarlet Installing XmlStarlet Converting XML Documents Chapter 7 JSON (JavaScript Object Notation) Chapter 8 Scripting Variables Arguments Conditional Execution Loops Chapter 9 Solving Common Problems Viewing Large Files Locating Files That Contain Particular Data Finding Files with Specific Characteristics Working with Internal Metadata Working with APIs Combining Data from Different Sources Other Tasks Chapter 10 Conclusions One-Line Wonders Locating, Viewing, and Performing Basic File Operations Combine Information from Multiple Files into a Single File Combine Three Files, Each Consisting of a Single Column into a Three-Column Table Extract 1,000 Random Lines or Records from a File Find Files with Specific Characteristics Find All Lines in All Files in the Current Directory as Well as All Subdirectories Containing a Regular Expression Identify All Files in Current Directories and Subdirectories That Contain a Value List All Files in Current Directory and Subdirectories over a 100 MB in Order of Decreasing Size List the Names, Pixel Dimensions, and File Sizes of All Files in the Current Directory and Subdirectories in Tab Delimited Format Print Line Number of File That Match Occurred On Split Large Files into Smaller Chunks with Each File Breaking on a Line View 200 Characters Starting at Position 38562 in a File View Lines 4369–4374 of a File Retrieving and Sending Information over a Network Retrieve a Document from the Web and Send It to a File Send an XML Document to an API Requiring HTTP Authentication Sorting, Counting, Deduplication, and File Comparison Combine Two Files on a Common Field Compare Two Sorted Files Count Occurrences for Each Entry in a File, Listed in Order of Decreasing Frequency Count Records Containing an Expression Count Words, Lines, and Characters in Files Identify All Unique Entries and Supply a Count of How Many Times Each Occurs Sort a File and Remove Duplicates, Show Only Duplicated Entries, or Show Only Unique Entries Useful Scripting Operations Capture Parameters Passed to a Script Divide a Line into Parameters Iterate through Every Item in Parameter List Perform a Loop Perform an Operation Conditionally Run a Script on Every Line of a File Send the Output of a Command as Arguments to Another Command Send the Output of a Command to Another Command Send the Output of a Command to a File Store the Output of a Command in a Variable Use Foreign Character Sets in a Terminal Window Transforming Text Convert File of Dates to YYYY-MM-DD Format Convert to Title Case Convert to Upper Case Convert List of Names from Direct Order to Indirect Order Extract and Manipulate All Lines in a File That Match a Complex Pattern Extract and Manipulate All Entries in All Files in an Entire Directory Hierarchy That Match a Pattern Remove Lines from a File That Match a Pattern Remove Carriage Return Characters Inserted by Windows Programs from a File Remove Newline Characters from a File Replace Newlines in a File with Character 7 (Bell) Replace Search_Expr with Replace_Expr Only on Lines That Contain Condition_Expr Replace Search_Expr with Replace_Expr Except on Lines That Contain Condition_Expr Replace Smart Quotes with Straight Quotes Working with Delimited Files Convert Comma Delimited File Where Some Values Are Quoted and Some Values Are Not to Tab Delimited Convert Multiline Records to Table Extract Individual Fields from Files Find the Most Common Values in the Second Field of a File Find All Lines in Tab Delimited File Not Containing Six Fields Fix Delimited File That Contains Line Breaks in Fields Remove Trailing and Leading Whitespace from Tab Delimited Data Fields Reorder Fields in a Tab Delimited File Working with JSON and XML Add an Attribute to an XML Document Add an Element to an XML Document Apply XSLT Stylesheet to XML Document Convert JSON to Tab Delimited Format Delete Elements, Attributes, or Values Based on XPath Expressions Display Structure of XML File Pretty Print JSON Document Pretty Print XML Document Glossary Symbols That Perform Important Tasks Useful Commands Regular Expression Cheat Sheet Index

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Book SynopsisAdvances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approachesTable of Contents1. Graph of Words Model for Natural Language Processing. 2. Application of NLP Using Graph Approaches. 3. Graph-based Extractive Approach for English and Hindi Text Summarization. 4. Graph Embeddings for Natural Language Processing. 5. Natural Language Processing with Graph and Machine Learning Algorithms-based Large-scale Text Document Summarization and Its Applications. 6. Ontology and Knowledge Graphs for Semantic Analysis in Natural Language Processing. 7. Ontology and Knowledge Graphs for Natural Language Processing. 8 Perfect Coloring by HB Color Matrix Algorithm Method. 9 Cross-lingual Word Sense Disambiguation Using Multilingual Co-occurrence Graphs. 10 Study of Current Learning Techniques for Natural Language Processing for Early Detection of Lung Cancer. 11 A Critical Analysis of Graph Topologies for Natural Language Processing and Their Applications. 12 Graph-based Text Document Extractive Summarization. 13 Applications of Graphical Natural Language Processing. 14 Analysis of Medical Images Using Machine Learning Techniques.

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Book SynopsisPreface.- Introduction.- Part 1: General Recommendation Techniques.- Trust Your Neighbors: A Comprehensive Survey of Neighborhood-based Methods for Recommender Systems (Desrosiers).- Advances in Collaborative Filtering (Koren).- Item Recommendation from Implicit Feedback (Rendle).- Deep Learning for Recommender Systems (Zhang).- Context Aware Re commender Sytems : From Foundatiom to Recent Developments (Bauman).- Semantics and Content-based Recommendations (Musto).- Part 2: Special Recommendation Techniques.- Session-based Recommender Systems (lannoch)..- Adversarial Recommender Systems: Attack,Defense, and Advances (Di Nola).- Group Recommender Systems: Beyond Preferance Aggregation (Masthoff).- People-to-People Reciprocal Recommenders (Koprinska).- Natural Language Processing for Recommender Systems (Sar-Shalom).- Design and Evaluation of Cross-domain Recommender Systems (Cremonesi).- Part 3: Value and Impact of Recommender Systems.- Value and Impact of Recommender SyTable of ContentsPreface.- Introduction.- Part 1: General Recommendation Techniques.- Trust Your Neighbors: A Comprehensive Survey of Neighborhood-based Methods for Recommender Systems (Desrosiers).- Advances in Collaborative Filtering (Koren).- Item Recommendation from Implicit Feedback (Rendle).- Deep Learning for Recommender Systems (Zhang).- Context Aware Re commender Sytems : From Foundatiom to Recent Developments (Bauman).- Semantics and Content-based Recommendations (Musto).- Part 2: Special Recommendation Techniques.- Session-based Recommender Systems (lannoch)..- Adversarial Recommender Systems: Attack,Defense, and Advances (Di Nola).- Group Recommender Systems: Beyond Preferance Aggregation (Masthoff).- People-to-People Reciprocal Recommenders (Koprinska).- Natural Language Processing for Recommender Systems (Sar-Shalom).- Design and Evaluation of Cross-domain Recommender Systems (Cremonesi).- Part 3: Value and Impact of Recommender Systems.- Value and Impact of Recommender Systems (Zanker).- Evaluating Recommender Systems (Shani).- Novelty and Diversity in Recommender Systems (Castells).- Multistakeholder Recommender Systems (Burke).- Fairness in Recommender Systems (Ekstrand).- Part 4: Human Computer Interaction.- Beyond Explaining Single Item Recommendations (Tintarev).- Personality and Recommender Systems (Tkalčič).- Individual and Group Decision Making and Recommender Systems (Jameson).- Part 5: Recommender Systems Applications .- Social Recommender Systems (Guy).- Food Recommender Systems (Trattner).- Music Recommendation Systems: Techniques, Use Cases, and Challenges (Schedl).- Multimedia Recommender Systems: Algorithms and Challenges (Deldjoo).- Fashion Recommender Systems (Dokoohaki).

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Book SynopsisThe fun way to research your family history Genealogy For Dummies, 8th Edition covers everything you need to know about starting a genealogical research projectincluding where and how to find information, how to communicate with other online genealogists, how to leverage social networking sites and apps, how to add digital images to your family tree, and how to build your own site for sharing information. It also explains the use of compiled genealogies, U.S. Census information, and public access catalogs. Brand new to this edition is content on how to conduct genealogical research on the road, and on how to take this research and integrate it into the data found at home. It also contains new information on DNA research and testing, new geocoding applications to record geographic data into a genealogical database, and other new technologies. The book covers which apps are worth your money, and how to get the most out of them. Use the latest toolTable of ContentsIntroduction 1 About This Book 2 Foolish Assumptions 2 Icons Used in This Book 3 Beyond the Book 3 Where to Go from Here 4 Part 1: Getting Started with Genealogy 5 Chapter 1: Beginning Your Ancestral Journey 7 It’s About Time(line) 7 Crafting an online timeline 9 Learning about Sources 13 Using Genealogical Applications 15 Entering Information into RootsMagic Essentials 17 Completing the Pedigree Page 20 Creating the Virtual You 21 Giving Your Ancestors Some Privacy 24 Beefing Up Your Profile 24 Citing Your Sources 26 Getting the Full Media Experience 28 Reaching Out to Others 29 Hinting Around about Your Ancestors 30 Giving Your Ancestors Some Mobility 31 Telling Your Story 34 Chapter 2: Hunting for Your Ancestral Treasures 35 A Brief Message about Research Steps 35 Selecting a Person to Begin Your Search 36 Trying a semi-unique name 36 Narrowing your starting point 36 Choosing someone you know about 38 Selecting a grandparent’s name 39 Beginning to Put the Puzzle Together 39 Getting the 4-1-1 from Your Kinfolk 41 Dusting off old photo albums 43 Striking it rich in closets, in basements, and under beds 45 Adding Your Ancestors One by One 47 Using a bit of (Roots)Magic to keep track of your family 48 Logging your data into Ancestry Family Tree 53 Chapter 3: Searching Primary Resource Sites 55 Touring Ancestry.com 56 Trying Ancestry.com for free 56 Searching Ancestry.com’s vast collection 58 Sifting through the results 62 RootsWeb.com at a Glance 68 Investigating FamilySearch 69 Creating a free account 69 FamilySearching records 70 Using FamilySearch results 71 Other FamilySearch search functions 75 Giving Back through FamilySearch Indexing 75 Saluting Fold3 76 Creating a trial account 76 Searching at Fold3 77 Finding Your Past 82 Exploring MyHeritage 84 Chapter 4: Using All of Your Censuses 87 Coming to Your Census 88 United States census schedules 88 State, territorial, and other census records 95 Finding Your Ancestors in U.S Census Records 97 Sifting through census record results 98 Digging into digitized census records 100 Consolidating your discoveries 104 Using census records to tell a story 106 Census Records from Afar 109 Africa 110 Asia 110 Europe 110 North America 113 Oceania 113 South America 113 Part 2: Bringing Your Ancestor to Life 115 Chapter 5: Digging Deeper into Your Ancestors’ Lives 117 These Records Are Vital 117 Reading vital records 118 Gauging vitals online 120 Investigating Immigration and Naturalization Records 123 Passenger lists 125 Naturalization records 127 Land Ho! Researching Land Records 129 Surveying land lovers in the U.S. 130 Using HistoryGeo.com to map your ancestor’s land 134 Marching to a Different Drummer: Searching for Military Records 135 Taxation with Notation 140 Trial and Error at the Courthouse 142 Getting the News on Your Ancestors 143 Chapter 6: Mapping the Past 147 Are We There Yet? Researching Where “There” Was to Your Ancestors 148 Using documents that you already possess 148 Where is Llandrindod, anyway? 149 There’s No Place like Home: Using Local Resources 153 Geographic-specific websites 154 Libraries and archives 156 Pulling the obituary 157 Genealogical and historical societies 158 Looking at local directories 159 Professional researchers 161 Localizing your search 162 Gaining historical perspective 162 Mapping Your Ancestor’s Way 164 Positioning your family: Using global positioning systems 171 Plotting against the family 172 Wrapping It Up (with a Surprise) 174 Chapter 7: Searching for That Elusive Ancestor 175 Letting Your Computer Do the Walking: Using Search Engines 176 Diving into general Internet search engines 176 Flying with Genealogy Vertical Search Engines 181 Finding the Site That’s Best for You 183 Personal genealogical sites 183 One-name study sites 185 Family associations and organizations 186 Surnames connected to events or places 187 Family Trees Ripe for the Picking: Finding Compiled Resources 188 Narrative compiled genealogies 189 Compiled genealogical databases 189 Browsing Comprehensive Genealogical Indexes 191 Chapter 8: Going Beyond Borders: International and Ethnic Records 193 Fishing for International and Ethnic Sources 194 Wiki-ing for answers 194 Surveying sites with comprehensive genealogy indexes 195 Using search engines 195 WorldGenWeb 195 Translating sites 197 Records from the English-Speaking World 197 Gathering information from England and Wales 198 A lot more than haggis — finding Scottish records 201 Researching the north o’ Ireland 201 Traversing the Emerald Isle 202 Other Irish genealogy resources 203 Heading north for Canadian records 204 Accessing Australian sources 207 Hispanic and Portuguese Roots 208 Within the United States 208 Exploring south of the border: Mexican sources 209 Continental resources 210 Central and South American research 211 Swimming through Caribbean genealogy 214 Achtung! Using Sites for the German-Speaking World 215 Along the beautiful Danube: Austrian roots 215 Consulting German resources 216 Focusing on French Resources 218 Scanning Scandinavian Countries 218 Denmark 218 Finland 219 Norway 220 Sweden 220 Iceland 221 Italian Cooking 221 Other European Sites 221 Asian Resources 223 Researching African Ancestry 224 Genealogical resource pages on the web 226 Transcribed records pertaining to ancestors with African roots 227 Special ethnic pages about African ancestry 228 Original records 229 American Indian Resources 229 Where to begin looking for information about American Indians 230 American Indian resource pages on the web 232 Transcribed American Indian records 233 Chapter 9: Specializing in Your Family History 235 Researching Religious Group Records 236 Finding Fraternal Orders and Service Clubs 240 A Photo Is Worth a Thousand Words 242 Accessing Adoption Records 245 Preparing to Be Schooled 246 Turning to Bible Records 248 Snooping through Great-Grandma’s Diary 248 Nosing through Newspaper Records 249 Part 3: Putting Your Family History to the Test 251 Chapter 10: Fitting into Your Genes: Genetic Genealogy 253 Ask What DNA Can Do for You 254 A Friendly Word of Caution 255 Delving into DNA 256 Getting down to bases 257 Variations in DNA 259 Family History: Documentation versus Genetics 261 Testing Companies 262 Selecting the Right Test for You 263 Finding Helpful DNA Sites 264 Chapter 11: Direct-Line Genetic Tests 265 Y chromosome (Y-DNA) testing 265 “Junk” DNA is worth something 266 The testing process 267 Comparing the results 268 Assessing the probability of a relationship 270 Haplogroups 271 Locating others with the same results 275 Mitochondrial (mtDNA) testing 276 Testing method 278 Making sense of the results 279 Finding others with the same results 280 Chapter 12: Autosomal DNA (atDNA) Testing 281 But First a Quick Review 281 Testing Process 283 What Can I Learn from Autosomal DNA Testing? 284 Ethnicity Estimation 285 Relationship Testing 288 Back to a familiar family 290 Objectives of the test 291 Playing the match game 292 Set your phasing to stun 293 We have something In Common With you 294 Sticking with tradition 296 Browsing through the chromosomes 296 Triangulating the data 298 Meeting the objectives 300 X-Chromosome DNA Testing 301 Utilities to the Rescue 303 Part 4: Casting Your Nets in the Genealogy Sea 305 Chapter 13: Finding Your Research Path 307 Introducing the Helm Online Family Tree Research Cycle 307 Planning your research 309 Collecting useful information 311 Researching: Through the brick wall and beyond 312 Consolidating information in a database 313 Validating your findings 313 Distilling the information that you gather 314 Too Many Ancestor Irons in the Research Fire 315 Verifying Your Information 315 Chapter 14: Share and Share Alike 317 Why Would Anyone Want Your Stuff? 318 Making Friends on Facebook 318 Jumping on the Facebook bandwagon 319 Making Facebook friends 320 Sorting your Facebook friends 321 Posting statuses on Facebook 322 Sharing photos via Facebook 322 Pinning Family History to Pinterest 324 Realizing Instant Gratification with Instagram 326 Networking Genealogy-Style 326 Sharing your history on Geni.com 327 Discovering contacts through Member Connect 331 Showing context in LifeStory 331 Blogging for Attention 334 Hunting blogs 334 Getting a blog of your own 335 Building Your Own Home 338 Free web-hosting services 338 Do you speak HTML? 340 Deciding which treasures to include 340 Including Your GEDCOM 340 Generating GEDCOM files 341 Checking a GEDCOM for possible errors 343 Creating traditional trees and reports 343 Earning a Good Citizenship Award 345 Mandatory lecture on privacy 345 Respecting copyrights 346 Citing your sources 347 Chapter 15: Help Wanted! 349 Getting Out of Your Comfort Zone 349 The Shotgun Approach 350 Making Friends (and Keeping Them) Online 351 Joining a Herd: Research Groups 353 Becoming a solid member of geographical societies 354 Rooting for family and surname associations 354 Joining the crowd — Crowd Sourced Indexing, that is 356 Gathering Kinfolk: Using the Family Reunion for Research 357 Rent-a-Researcher 357 DNA Consulting 361 Helping Yourself 361 Reading up on genealogical things 362 Getting educated online 362 Part 5: The Part of Tens 365 Chapter 16: Ten Sites Worth a Visit 367 rootsfinder 367 FamilySearch Help Center 368 WeRelate 368 kindex 368 One-Step Webpages by Stephen P Morse 369 Photogrammar 369 Story Corps 369 American Battle Monuments Commission 370 Atlas of the Historical Geography of the United States 370 ArchiveGrid 371 Chapter 17: Ten Mobile Applications for Genealogy Research 373 Ancestry 373 FamilySearch Tree 375 RootsMagic 375 BillionGraves 376 Evernote 377 The Family Nexus 377 Saving Memories Forever 378 OldNews USA 379 QromaTag 379 Kindle 379 Index 381

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Book SynopsisWith the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query retrieval support for e-health implementation Ontologies as a database management system technology for medicalTable of ContentsPreface xix Acknowledgment xxiii 1 Role of Ontology in Health Care 1Sonia Singla 1.1 Introduction 2 1.2 Ontology in Diabetes 3 1.2.1 Ontology Process 4 1.2.2 Impediments of the Present Investigation 5 1.3 Role of Ontology in Cardiovascular Diseases 6 1.4 Role of Ontology in Parkinson Diseases 8 1.4.1 The Spread of Disease With Age and Onset of Disease 10 1.4.2 Cost of PD for Health Care, Household 11 1.4.3 Treatment and Medicines 11 1.5 Role of Ontology in Depression 13 1.6 Conclusion 15 1.7 Future Scope 15 References 15 2 A Study on Basal Ganglia Circuit and Its Relation With Movement Disorders 19Dinesh Bhatia 2.1 Introduction 19 2.2 Anatomy and Functioning of Basal Ganglia 21 2.2.1 The Striatum-Major Entrance to Basal Ganglia Circuitry 22 2.2.2 Direct and Indirect Striatofugal Projections 23 2.2.3 The STN: Another Entrance to Basal Ganglia Circuitry 25 2.3 Movement Disorders 26 2.3.1 Parkinson Disease 26 2.3.2 Dyskinetic Disorder 27 2.3.3 Dystonia 28 2.4 Effect of Basal Ganglia Dysfunctioning on Movement Disorders 29 2.5 Conclusion and Future Scope 31 References 31 3 Extraction of Significant Association Rules Using Pre- and Post-Mining Techniques—An Analysis 37M. Nandhini and S. N. Sivanandam 3.1 Introduction 38 3.2 Background 39 3.2.1 Interestingness Measures 39 3.2.2 Pre-Mining Techniques 40 3.2.2.1 Candidate Set Reduction Schemes 40 3.2.2.2 Optimal Threshold Computation Schemes 41 3.2.2.3 Weight-Based Mining Schemes 42 3.2.3 Post-Mining Techniques 42 3.2.3.1 Rule Pruning Schemes 43 3.2.3.2 Schemes Using Knowledge Base 43 3.3 Methodology 44 3.3.1 Data Preprocessing 44 3.3.2 Pre-Mining 46 3.3.2.1 Pre-Mining Technique 1: Optimal Support and Confidence Threshold Value Computation Using PSO 46 3.3.2.2 Pre-Mining Technique 2: Attribute Weight Computation Using IG Measure 48 3.3.3 Association Rule Generation 50 3.3.3.1 ARM Preliminaries 50 3.3.3.2 WARM Preliminaries 52 3.3.4 Post-Mining 56 3.3.4.1 Filters 56 3.3.4.2 Operators 58 3.3.4.3 Rule Schemas 58 3.4 Experiments and Results 59 3.4.1 Parameter Settings for PSO-Based Pre-Mining Technique 60 3.4.2 Parameter Settings for PAW-Based Pre-Mining Technique 60 3.5 Conclusions 63 References 65 4 Ontology in Medicine as a Database Management System 69Shobowale K. O. 4.1 Introduction 70 4.1.1 Ontology Engineering and Development Methodology 72 4.2 Literature Review on Medical Data Processing 72 4.3 Information on Medical Ontology 75 4.3.1 Types of Medical Ontology 75 4.3.2 Knowledge Representation 76 4.3.3 Methodology of Developing Medical Ontology 76 4.3.4 Medical Ontology Standards 77 4.4 Ontologies as a Knowledge-Based System 78 4.4.1 Domain Ontology in Medicine 79 4.4.2 Brief Introduction of Some Medical Standards 81 4.4.2.1 Medical Subject Headings (MeSH) 81 4.4.2.2 Medical Dictionary for Regulatory Activities (MedDRA) 81 4.4.2.3 Medical Entities Dictionary (MED) 81 4.4.3 Reusing Medical Ontology 82 4.4.4 Ontology Evaluation 85 4.5 Conclusion 86 4.6 Future Scope 86 References 87 5 Using IoT and Semantic Web Technologies for Healthcare and Medical Sector 91Nikita Malik and Sanjay Kumar Malik 5.1 Introduction 92 5.1.1 Significance of Healthcare and Medical Sector and Its Digitization 92 5.1.2 e-Health and m-Health 92 5.1.3 Internet of Things and Its Use 94 5.1.4 Semantic Web and Its Technologies 96 5.2 Use of IoT in Healthcare and Medical Domain 98 5.2.1 Scope of IoT in Healthcare and Medical Sector 98 5.2.2 Benefits of IoT in Healthcare and Medical Systems 100 5.2.3 IoT Healthcare Challenges and Open Issues 100 5.3 Role of SWTs in Healthcare Services 101 5.3.1 Scope and Benefits of Incorporating Semantics in Healthcare 101 5.3.2 Ontologies and Datasets for Healthcare and Medical Domain 103 5.3.3 Challenges in the Use of SWTs in Healthcare Sector 104 5.4 Incorporating IoT and/or SWTs in Healthcare and Medical Sector 106 5.4.1 Proposed Architecture or Framework or Model 106 5.4.2 Access Mechanisms or Approaches 108 5.4.3 Applications or Systems 109 5.5 Healthcare Data Analytics Using Data Mining and Machine Learning 110 5.6 Conclusion 112 5.7 Future Work 113 References 113 6 An Ontological Model, Design, and Implementation of CSPF for Healthcare 117Pooja Mohan 6.1 Introduction 117 6.2 Related Work 119 6.3 Mathematical Representation of CSPF Model 122 6.3.1 Basic Sets of CSPF Model 123 6.3.2 Conditional Contextual Security and Privacy Constraints 123 6.3.3 CSPF Model States CsetofStates 124 6.3.4 Permission Cpermission 124 6.3.5 Security Evaluation Function (SEFcontexts) 124 6.3.6 Secure State 125 6.3.7 CSPF Model Operations 125 6.3.7.1 Administrative Operations 125 6.3.7.2 Users’ Operations 127 6.4 Ontological Model 127 6.4.1 Development of Class Hierarchy 127 6.4.1.1 Object Properties of Sensor Class 129 6.4.1.2 Data Properties 129 6.4.1.3 The Individuals 129 6.5 The Design of Context-Aware Security and Privacy Model for Wireless Sensor Network 129 6.6 Implementation 133 6.7 Analysis and Results 135 6.7.1 Inference Time/Latency/Query Response Time vs. No. of Policies 135 6.7.2 Average Inference Time vs. Contexts 136 6.8 Conclusion and Future Scope 137 References 138 7 Ontology-Based Query Retrieval Support for E-Health Implementation 143Aatif Ahmad Khan and Sanjay Kumar Malik 7.1 Introduction 143 7.1.1 Health Care Record Management 144 7.1.1.1 Electronic Health Record 144 7.1.1.2 Electronic Medical Record 145 7.1.1.3 Picture Archiving and Communication System 145 7.1.1.4 Pharmacy Systems 145 7.1.2 Information Retrieval 145 7.1.3 Ontology 146 7.2 Ontology-Based Query Retrieval Support 146 7.3 E-Health 150 7.3.1 Objectives and Scope 150 7.3.2 Benefits of E-Health 151 7.3.3 E-Health Implementation 151 7.4 Ontology-Driven Information Retrieval for E-Health 154 7.4.1 Ontology for E-Heath Implementation 155 7.4.2 Frameworks for Information Retrieval Using Ontology for E-Health 157 7.4.3 Applications of Ontology-Driven Information Retrieval in Health Care 158 7.4.4 Benefits and Limitations 160 7.5 Discussion 160 7.6 Conclusion 164 References 164 8 Ontology-Based Case Retrieval in an E-Mental Health Intelligent Information System 167Georgia Kaoura, Konstantinos Kovas and Basilis Boutsinas 8.1 Introduction 167 8.2 Literature Survey 170 8.3 Problem Identified 173 8.4 Proposed Solution 174 8.4.1 The PAVEFS Ontology 174 8.4.2 Knowledge Base 179 8.4.3 Reasoning 180 8.4.4 User Interaction 182 8.5 Pros and Cons of Solution 183 8.5.1 Evaluation Methodology and Results 183 8.5.2 Evaluation Methodology 185 8.5.2.1 Evaluation Tools 186 8.5.2.2 Results 187 8.6 Conclusions 189 8.7 Future Scope 190 References 190 9 Ontology Engineering Applications in Medical Domain 193Mariam Gawich and Marco Alfonse 9.1 Introduction 193 9.2 Ontology Activities 195 9.2.1 Ontology Learning 195 9.2.2 Ontology Matching 195 9.2.3 Ontology Merging (Unification) 195 9.2.4 Ontology Validation 196 9.2.5 Ontology Verification 196 9.2.6 Ontology Alignment 196 9.2.7 Ontology Annotation 196 9.2.8 Ontology Evaluation 196 9.2.9 Ontology Evolution 196 9.3 Ontology Development Methodologies 197 9.3.1 TOVE 197 9.3.2 Methontology 198 9.3.3 Brusa et al. Methodology 198 9.3.4 UPON Methodology 199 9.3.5 Uschold and King Methodology 200 9.4 Ontology Languages 203 9.4.1 RDF-RDF Schema 203 9.4.2 OWL 205 9.4.3 OWL 2 205 9.5 Ontology Tools 208 9.5.1 Apollo 208 9.5.2 NeON 209 9.5.3 Protégé 210 9.6 Ontology Engineering Applications in Medical Domain 212 9.6.1 Ontology-Based Decision Support System (DSS) 213 9.6.1.1 OntoDiabetic 213 9.6.1.2 Ontology-Based CDSS for Diabetes Diagnosis 214 9.6.1.3 Ontology-Based Medical DSS within E-Care Telemonitoring Platform 215 9.6.2 Medical Ontology in the Dynamic Healthcare Environment 216 9.6.3 Knowledge Management Systems 217 9.6.3.1 Ontology-Based System for Cancer Diseases 217 9.6.3.2 Personalized Care System for Chronic Patients at Home 218 9.7 Ontology Engineering Applications in Other Domains 219 9.7.1 Ontology Engineering Applications in E-Commerce 219 9.7.1.1 Automated Approach to Product Taxonomy Mapping in E-Commerce 219 9.7.1.2 LexOnt Matching Approach 221 9.7.2 Ontology Engineering Applications in Social Media Domain 222 9.7.2.1 Emotive Ontology Approach 222 9.7.2.2 Ontology-Based Approach for Social Media Analysis 224 9.7.2.3 Methodological Framework for Semantic Comparison of Emotional Values 225 References 226 10 Ontologies on Biomedical Informatics 233Marco Alfonse and Mariam Gawich 10.1 Introduction 233 10.2 Defining Ontology 234 10.3 Biomedical Ontologies and Ontology-Based Systems 235 10.3.1 MetaMap 235 10.3.2 GALEN 236 10.3.3 NIH-CDE 236 10.3.4 LOINC 237 10.3.5 Current Procedural Terminology (CPT) 238 10.3.6 Medline Plus Connect 238 10.3.7 Gene Ontology 239 10.3.8 UMLS 240 10.3.9 SNOMED-CT 240 10.3.10 OBO Foundry 240 10.3.11 Textpresso 240 10.3.12 National Cancer Institute Thesaurus 241 References 241 11 Machine Learning Techniques Best for Large Data Prediction: A Case Study of Breast Cancer Categorical Data: k-Nearest Neighbors 245Yagyanath Rimal 11.1 Introduction 246 11.2 R Programming 250 11.3 Conclusion 255 References 255 12 Need of Ontology-Based Systems in Healthcare System 257Tshepiso Larona Mokgetse 12.1 Introduction 258 12.2 What is Ontology? 259 12.3 Need for Ontology in Healthcare Systems 260 12.3.1 Primary Healthcare 262 12.3.1.1 Semantic Web System 262 12.3.2 Emergency Services 263 12.3.2.1 Service-Oriented Architecture 263 12.3.2.2 IOT Ontology 264 12.3.3 Public Healthcare 265 12.3.3.1 IOT Data Model 265 12.3.4 Chronic Disease Healthcare 266 12.3.4.1 Clinical Reminder System 266 12.3.4.2 Chronic Care Model 267 12.3.5 Specialized Healthcare 268 12.3.5.1 E-Health Record System 268 12.3.5.2 Maternal and Child Health 269 12.3.6 Cardiovascular System 270 12.3.6.1 Distributed Healthcare System 270 12.3.6.2 Records Management System 270 12.3.7 Stroke Rehabilitation 271 12.3.7.1 Patient Information System 271 12.3.7.2 Toronto Virtual System 271 12.4 Conclusion 272 References 272 13 Exploration of Information Retrieval Approaches With Focus on Medical Information Retrieval 275Mamata Rath and Jyotir Moy Chatterjee 13.1 Introduction 276 13.1.1 Machine Learning-Based Medical Information System 278 13.1.2 Cognitive Information Retrieval 278 13.2 Review of Literature 279 13.3 Cognitive Methods of IR 281 13.4 Cognitive and Interactive IR Systems 286 13.5 Conclusion 288 References 289 14 Ontology as a Tool to Enable Health Internet of Things Viable 5G Communication Networks 293Nidhi Sharma and R. K. Aggarwal 14.1 Introduction 293 14.2 From Concept Representations to Medical Ontologies 295 14.2.1 Current Medical Research Trends 296 14.2.2 Ontology as a Paradigm Shift in Health Informatics 296 14.3 Primer Literature Review 297 14.3.1 Remote Health Monitoring 298 14.3.2 Collecting and Understanding Medical Data 298 14.3.3 Patient Monitoring 298 14.3.4 Tele-Health 299 14.3.5 Advanced Human Services Records Frameworks 299 14.3.6 Applied Autonomy and Healthcare Mechanization 300 14.3.7 IoT Powers the Preventive Healthcare 301 14.3.8 Hospital Statistics Control System (HSCS) 301 14.3.9 End-to-End Accessibility and Moderateness 301 14.3.10 Information Mixing and Assessment 302 14.3.11 Following and Alerts 302 14.3.12 Remote Remedial Assistance 302 14.4 Establishments of Health IoT 303 14.4.1 Technological Challenges 304 14.4.2 Probable Solutions 306 14.4.3 Bit-by-Bit Action Statements 307 14.5 Incubation of IoT in Health Industry 307 14.5.1 Hearables 308 14.5.2 Ingestible Sensors 308 14.5.3 Moodables 308 14.5.4 PC Vision Innovation 308 14.5.5 Social Insurance Outlining 308 14.6 Concluding Remarks 309 References 309 15 Tools and Techniques for Streaming Data: An Overview 313K. Saranya, S. Chellammal and Pethuru Raj Chelliah 15.1 Introduction 314 15.2 Traditional Techniques 315 15.2.1 Random Sampling 315 15.2.2 Histograms 316 15.2.3 Sliding Window 316 15.2.4 Sketches 317 15.2.4.1 Bloom Filters 317 15.2.4.2 Count-Min Sketch 317 15.3 Data Mining Techniques 317 15.3.1 Clustering 318 15.3.1.1 STREAM 318 15.3.1.2 BRICH 318 15.3.1.3 CLUSTREAM 319 15.3.2 Classification 319 15.3.2.1 Naïve Bayesian 319 15.3.2.2 Hoeffding 320 15.3.2.3 Very Fast Decision Tree 320 15.3.2.4 Concept Adaptive Very Fast Decision Tree 320 15.4 Big Data Platforms 320 15.4.1 Apache Storm 321 15.4.2 Apache Spark 321 15.4.2.1 Apache Spark Core 321 15.4.2.2 Spark SQL 322 15.4.2.3 Machine Learning Library 322 15.4.2.4 Streaming Data API 322 15.4.2.5 GraphX 323 15.4.3 Apache Flume 323 15.4.4 Apache Kafka 323 15.4.5 Apache Flink 326 15.5 Conclusion 327 References 328 16 An Ontology-Based IR for Health Care 331J. P. Patra, Gurudatta Verma and Sumitra Samal 16.1 Introduction 331 16.2 General Definition of Information Retrieval Model 333 16.3 Information Retrieval Model Based on Ontology 334 16.4 Literature Survey 336 16.5 Methodolgy for IR 339 References 344

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Book SynopsisIntroduction to Data Mining.- Data for Data Mining.- Introduction to Classification: Naïve Bayes and Nearest Neighbour.- Using Decision Trees for Classification.- Decision Tree Induction: Using Entropy for Attribute Selection.- Decision Tree Induction: Using Frequency Tables for Attribute Selection.- Estimating the Predictive Accuracy of a Classifier.- Continuous Attributes.- Avoiding Overfitting of Decision Trees.- More About Entropy.- Inducing Modular Rules for Classification.- Measuring the Performance of a Classifier.- Dealing with Large Volumes of Data.- Ensemble Classification.- Comparing Classifiers.- Associate Rule Mining I.- Associate Rule Mining II.- Associate Rule Mining III.- Clustering.- Mining.- Classifying Streaming Data.- Classifying Streaming Data II: Time-dependent Data.- An Introduction to Neural Networks.- Appendix A Essential Mathematics.- Appendix B Datasets.- Appendix C Sources of Further Information.- Appendix D Glossary and Notation.- Appendix E SolutioTable of ContentsIntroduction to Data Mining.- Data for Data Mining.- Introduction to Classification: Naïve Bayes and Nearest Neighbour.- Using Decision Trees for Classification.- Decision Tree Induction: Using Entropy for Attribute Selection.- Decision Tree Induction: Using Frequency Tables for Attribute Selection.- Estimating the Predictive Accuracy of a Classifier.- Continuous Attributes.- Avoiding Overfitting of Decision Trees.- More About Entropy.- Inducing Modular Rules for Classification.- Measuring the Performance of a Classifier.- Dealing with Large Volumes of Data.- Ensemble Classification.- Comparing Classifiers.- Associate Rule Mining I.- Associate Rule Mining II.- Associate Rule Mining III.- Clustering.- Mining.- Classifying Streaming Data.- Classifying Streaming Data II: Time-dependent Data.- An Introduction to Neural Networks.- Appendix A – Essential Mathematics.- Appendix B – Datasets.- Appendix C – Sources of Further Information.- Appendix D – Glossary and Notation.- Appendix E – Solutions to Self-assessment Exercises.- Index.

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Book SynopsisIntroduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data.

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Book Synopsis Learn the basic principles of modular design, and then put them into action to create sites that are easy to use, look great, and can be adapted within the context of your business needs. With author James Cabrera-one of the thought leaders in the modular-design movement-you''ll create a single, scalable project for a sample nameplate site and then adapt that same project to work successfully as a portfolio site, an e-commerce site, and finally as a news/publishing content site. Along the way, you''ll learn the scientific approach to devising a sound and scalable design strategy, followed by establishing a basic foundation using various criteria relevant to that type of site. As each chapter progresses, you''ll add new concepts appropriate for the project type.   Modular web and app design isn''t just for so-called creatives. It''s a teachable science with principles that can be replicated in a creative manner. This approach makes the design decisionTable of Contents Chapter 1: A Modular Future.- Chapter 2: Fonts, Colors & Invisible UI.- Chapter 3: Defining Your Basic Unit.- Chapter 4: Adaption, Reusability, Iteration, and Variation.- Chapter 5: Organization, Clustering, Pages, and Navigation.- Chapter 6: What's Next?.- Appendix: Breaking Down Examples into Modular Systems.

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Book Synopsis Learn all of the available upgrade and migration methods in detail to move to Oracle Database version 12c. You will become familiar with database upgrade best practices to complete the upgrade in an effective manner and understand the Oracle Database 12c patching process. So it''s time to upgrade Oracle Database to version 12c and you need to choose the appropriate method while considering issues such as downtime. This book explains all of the available upgrade and migration methods so you can choose the one that suits your environment. You will be aware of the practical issues and proactive measures to take to upgrade successfully and reduce unexpected issues.  With every release of Oracle Database there are new features and fixes to bugs identified in previous versions. As each release becomes obsolete, existing databases need to be upgraded. Oracle Database Upgrade and Migration Methods explains each method along Table of Contents PART I: packetC Background 1 CHAPTER 1: Getting Started 3 Introduction to Database upgrade Necessities of Database upgrade Benefits of Database upgrade Hurdles that affect Database upgrade decision Types of Database upgrade Things to consider before upgrade Engineers involved in upgrade activity Upgrade compatibility matrix Best practices of Database upgrade Database Migration Situations demand Migration Things to consider before migration summary PART II: Language Reference 53 n CHAPTER 2: Database Upgrade methods 55 DBUA Manual/Command line upgrade Export/Import Datapump Transportable Tablespace Golden Gate Create Table as Select (CTAS) Transient Logical Standby Full Transportable Tablespace Summary n CHAPTER 3: Comparison between upgrade methods 151 Comparison between methods 9 Real Application testing (RAT) 10 How to choose best Upgrade method 11 Summary n CHAPTER 4: Upgrade using Database backup 159 Cold backup Hot backup (User-Managed) Logical backup (expdp/impdp) RMAN backup (using duplicate option) Summary n CHAPTER 5: Database Migration methods 171 Export/Import Datapump Transportable Tablespace (TTS) Golden Gate Copy table as select (CTAS) Transport Database Heterogenous Standby database Oracle Streams Summary n CHAPTER 6: Migration of Oracle database from Non-ASM to ASM 175 Introduction Moving Datafiles Online from NON-ASM < to ASM Migrating Oracle 12c CDB with PDBs from NON ASM to ASM using EM Cloud Control 13c ............... Migrating Oracle 12c CDB with PDBs from NON ASM to ASM using RMAN Summary n CHAPTER 7: GI and DB upgrade in RAC environment 205 Introduction CVU Pre-Upgrade Check tool Execution Steps for ORAchk Rolling upgrade for Oracle GI Upgrading 11g RAC to 12c RAC using DBUA Upgrading 11g RAC to 12c RAC Manual Upgrading 11g RAC to 12c RAC using EM 13c Summary PART III: Developing Applications 215 n CHAPTER 8: Database upgrade in DG environment 217 Dummy Text Dummy Text Virtual Dummy Text Dummy Text Dummy Text Dummy Text Flow Dummy Text Summary n CHAPTER 9: Database upgrade in EBS environment 223 Prerequisite steps Preupgrade steps Upgrade steps Post upgrade steps Summary CHAPTER 10: Database upgrade in 12c Multitenant environment Migrate lower version database to Multitenant architecture Container database upgrade Pluggable database upgrade Summary n CHAPTER 11: Databases migrate in Multitenant environment 237 Pluggable database migrate Need for Migrate Migration steps Summary n CHAPTER 12: Oracle Database Patching Stratergies 245 Patching Introduction Opatch tool Types of patches Patch apply stratergies (online and offline patching).... PSU and SPU patching Patch apply in RAC and DG environment Datapatch Queryable patch inventory Summary n CHAPTER 13: Database Downgrade 263 Introduction Limitations of Oracle database downgrade Database downgrade steps Downgrade using database flashback Summary n CHAPTER 14: Database upgrade in 12.2 281 Preupgrade checks Upgrade Emulation DBUA Manual Database upgrade Pluggable database upgrade Downgrade 12.2 database to earlier version............... Summary n n APPENDIX A: Reference Tables 383 n APPENDIX B: Dummy Text 395 INDEX 433

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Book SynopsisAnd just as too much junk food can lead to obesity, too much junk information can lead to cluelessness. The Information Diet shows you how to thrive in this information glut-what to look for, what to avoid, and how to be selective.

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Book SynopsisLearning about distributed systems, becoming familiar with technologies such as containers and functions, and knowing how to put everything together can be daunting. With this practical guide, you'll get up to speed on patterns for building cloud native applications and best practices for common tasks such as messaging, eventing, and DevOps.

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Book SynopsisPreparing for your financial accounting exam? Make the grade with this SAP S/4HANA 1909 and 2020 certification study guide! From general ledger accounting to financial closing, this guide reviews the key technical and functional knowledge you need to get a high score on your SAP S/4HANA for Financial Accounting Associates exam.

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Book Synopsis

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Book Synopsis

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Book SynopsisSearch has become ubiquitous but that does not mean that search has been solved. Enterprise Search, which is broadly speaking the use of information retrieval technology to find information within organisations, is a good example to illustrate this. It is an area that is of huge importance for businesses, yet has attracted relatively little academic interest. Searching the Enterprise explores the main issues involved in enterprise search both from a research as well as a practical point of view. It first plots the landscape of enterprise search and its links to related areas, which allows it to identify key features before surveying the field in more detail. Throughout the monograph, enterprise search is discussed as part of the wider information retrieval research field, and Web search is used as a common reference point as this is likely the search application area that the average reader is most familiar with.Table of Contents1. Introduction; 2: Plotting the Landscape; 3: Enterprise Search Basics; 4: Evaluation; 5: Making Enterprise Search Work; 6: The Future; 7: Conclusion; Acknowledgements; References.

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Book SynopsisHow can a single person understand what’s going on in a collection of millions of documents? This is an increasingly widespread problem: sifting through an organization’s e- mails, understanding a decade worth of newspapers, or characterizing a scientific field’s research. This monograph explores the ways that humans and computers make sense of document collections through tools called topic models. Topic models are a statistical framework that help users understand large document collections; not just to find individual documents but to understand the general themes present in the collection. Applications of Topic Models describes the recent academic and industrial applications of topic models. In addition to topic models’ effective application to traditional problems like information retrieval, visualization, statistical inference, multilingual modeling, and linguistic understanding, Applications of Topic Models also reviews topic models’ ability to unlock large text collections for qualitative analysis. It reviews their successful use by researchers to help understand fiction, non-fiction, scientific publications, and political texts. Applications of Topic Models is aimed at the reader with some knowledge of document processing, basic understanding of some probability, and interested in many application domains. It discusses the information needs of each application area, and how those specific needs affect models, curation procedures, and interpretations. By the end of the monograph, it is hoped that readers will be excited enough to attempt to embark on building their own topic models. It should also be of interest to topic model experts as the coverage of diverse applications may expose models and approaches they had not seen before.Table of Contents1: The What and Wherefore of Topic Models; 2: Ad-hoc Information Retrieval; 3: Evaluation and Interpretation; 4: Historical Documents; 5: Understanding Scientific Publications; 6: Fiction and Literature; 7: Computational Social Science; 8: Multilingual Data and Machine Translation; 9: Building a Topic Model; 10: Conclusion; References.

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Book SynopsisNew Directions in Information Organization, co-edited by Dr. Jung-ran Park and Dr. Lynne Howarth seeks to provide an overview and understanding of the future directions, leading edge theories and models for research and practice in information organization. New information standards and digital library technologies are being developed at a rapid pace as diverse communities of practice seek new ways to organize massive quantities of digital resources. Today's digital information explosion creates an increased demand for new perspectives, methods and tools for research and practice in information organization. This new direction in information organization is even more critical owing to changing user needs and expectations in conjunction with the collaborative and decentralized nature of bibliographic control. The general aim of this book is to present the current state of the digital information revolution with the associated opportunities and challenges to information organization. Through an interdisciplinary perspective, it presents broad, holist and more integrated perspective on the nature of information organization and examines new direction in information organization research and thinking. The book highlights the need to understand information organization and the Web 2.0 in the context of the rapidly changing information world and provides an overview of key trends and further research.Table of ContentsList of Contributors. Editorial Advisory Board. Introduction. Organizing Bibliographical Data with RDA: How Far Have We Stridden Toward the Semantic Web?. Keeping Libraries Relevant in the Semantic Web with RDA: Resource Description and Access. Filling in the Blanks in RDA or Remaining Blank? The Strange Case of FRSAD. Organizing and Sharing Information Using Linked Data. Social Cataloging; Social Cataloger. Social Indexing: A Solution to the Challenges of Current Information Organization. Organizing Photographs: Past and Present. VuFind — An OPAC 2.0?. Faceted Search in Library Catalogs. Doing More With Less: Increasing the Value of the Consortial Catalog. All Metadata Politics Is Local: Developing Meaningful Quality Standards. New Directions in Information Organization. Library and Information Science. New Directions in Information Organization. Copyright page. Index. Conclusion: What New Directions in Information Organization Augurs for the Future.

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Book SynopsisCOM018000

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Book SynopsisDigital technologies are reshaping every field of social and economic lives, so do they in the world of scientific knowledge. “The New Challenges of Knowledge” aims at understanding how the new digital technologies alter the production, diffusion and valorization of knowledge. We propose to give an insight into the economical, geopolitical and political stakes of numeric in knowledge in different countries. Law is at the center of this evolution, especially in the case of national and international confusion about Internet, Science and knowledge.Trade Review“Sharing economy models are rippling through the world of scientific knowledge and research; open access brings challenges for developers, researchers, and policy makers – all treated here in the context of law-making” The Magpi, issue 60, Aug 2017Table of ContentsIntroduction . xiii Part 1. Production: Global Knowledge and Science in the Digital Era 1 Chapter 1. Current Knowledge Dynamics 3 1.1. Transparency of scientific data 4 1.2. Transparency of experimental protocol 6 1.3. A necessary form of research engineering 7 1.4. Confusion between data and scientific results: avoiding manipulation of research results 8 Chapter 2. Digital Conditions for Knowledge Production 11 2.1. An economic system oriented toward innovation 11 2.2. What of knowledge and indeed the concept of the commons? 13 2.3. From analog to digital 14 2.4. User–producer: civil society enters the knowledge production system 16 2.5. The interactions between the various spheres of knowledge production 18 2.6. Collaboration between society and knowledge: producing authorities should be put into perspective 20 Chapter 3. The Dual Relationship between the User and the Developer 23 3.1. Legal arrangements for knowledge-sharing using development platforms 23 3.2. The user contributes to the creation and development of content process 25 Chapter 4. Researchers’ Uses and Needs for Scientific and Technical Information 29 4.1. The CNRS survey 29 4.2. Diverse uses and dual needs 31 4.3. An explanation through differentiated scientific analysis 33 Chapter 5. New Tools for Knowledge Capture 37 5.1. The growth of metadata exploitation 37 5.2. Are we moving toward a semantic Web? 38 5.3. Tools and limits for metadata processing 39 5.4. The challenges of the semantic Web 40 Chapter 6. Modes of Knowledge Sharing and Technologies 43 6.1. Data storage technologies and access allowing knowledge sharing 43 6.2. Exchange platforms and catalogs 44 6.3. Knowledge-processing and digital editions 45 Part 2. Sharing Mechanisms: Knowledge Sharing and the Knowledge-based Economy 47 Chapter 7. Business Model for Scientific Publication 49 7.1. The current economic model is changing so as to adapt to new conditions for knowledge sharing 49 7.2. Creation of a new model 51 7.3. The issues raised by the creation of a new economic model 52 7.4. A new economic model struggling to fine its niche 54 Chapter 8. Actor Strategy: International Scientific Publishing, Services with High Added Value and Research Communities 57 8.1. Publishing, editing and existing: live issues within the publication of Scientific and Technical Information (STI) 58 8.2. Who is subject to it? The other players in scientific publishing 59 8.3. The characteristics of SMS (Science of Man and Society) 60 8.4. Existing without publishing? New STI directions 62 8.5. Alternatives to scientific publishing 63 Chapter 9. New Approaches to Scientific Production 67 9.1. New means of access to scientific production: innovative models 67 9.2. Two main objectives: accelerating knowledge sharing and promoting scientific collaboration 71 9.3. The need for new analytical tools and the risk of reprivatization of scientific knowledge. 72 9.4. The absence of the usage doctrine and the risk of reprivatization of science: the case of social networks 74 Chapter 10. The Geopolitics of Science 77 10.1. National convergent research models 78 10.2. Science is a source of international cooperation 81 10.3. International scientific cooperation is accelerating 84 Chapter 11. Copyright Serving the Market 85 Part 3. Enhancement Knowledge Rights and Public Policies in the Wake of Digital Technology 89 Chapter 12. Legal Protection of Scientific Research Results in the Humanities and Social Sciences 91 12.1.Different legal protections for different kinds of science 91 12.2. Why protect? 92 12.3. How to protect 93 12.4. Protect against whom? 98 12.5. Changing the challenges of Internet protection 99 12.6. Legal obstacles related to the author’s right 100 Chapter 13. Development of Knowledge and Public Policies 103 13.1. Knowledge enhancement concerns everyone 104 13.2. What are the public policies for enhancing knowledge? 105 13.3. State establishment of connections between actors: a key tool in knowledge enhancement 107 13.4. Comparing the United States and the European Union 109 Chapter 14. From Author to Enhancer 111 14.1. Enhancing scientific research is a complex process 112 14.2. Scientific research enhancement follows a legislative framework intended to promote innovation 114 Chapter 15. The Right to Knowledge: Moving Toward a Universal Law? 117 15.1. Unclear regulatory frameworks 118 15.2. Developing legal frameworks related to the Internet is complicated 121 15.3. Proposals for developing legal frameworks for the Internet 123 Chapter 16. Governing by Algorithm 127 16.1. Statistics that foreshadow algorithms 128 16.2. Algorithmic governance and democratic opportunities 130 Chapter 17. Public Data and Science in e-Government 133 17.1. Disseminating data and disseminating science: a new requirement 134 17.2. Public data in the e-government 137 17.3. Science within e-government 139 Chapter 18. Surveillance, Sousveillance, Improper Capturing 141 18.1. The traditional legal framework for information capture 142 18.2. The clear need for a specific law 145 Chapter 19. Public Knowledge Policies in the Digital Age 149 19.1. GAFA domination and the oligopolization of the market 150 19.2. Isolated digital ecosystems 152 19.3. Regulation through competition law 153 19.4. Data protection: moving toward a law for the digital community 154 Chapter 20. The Politics of Creating Artificial Intelligence 157 20.1. History 158 20.2. Artificial intelligence has become a priority for public and private actors 160 20.4. The appearance of legal problems 162 Chapter 21. Security Policies in Artificial Intelligence 165 21.1. Security as a comment on machines and data 166 21.2. From the security of machines to the security of humans 169 Conclusion 175 Postscript 177 Glossary 179 Bibliography 185 Index 201

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Book SynopsisBig data is a field of research that is growing rapidly, and as the Covid-19 crisis has shown, health care is an area that could benefit greatly from its increased use and application. Big data, as derived partly from the internet of things and analysed according to specific algorithms, has a large and beneficial role to play in preventative medicine, in monitoring the health of specific groups, and in improving diagnostics. Big Data Analytics and Intelligence: A Perspective for Health Care focuses on various areas of health care, ranging from nutrition to cancer, and providing diverse perspectives on all of them. This book explores the entire life-cycle of big data, from information retrieval to analysis, and it shows how big data’s applications can enhance, streamline and improve services for patients and health-care professionals. Each chapter focuses on a specific area of health care and how big data is applicable to it, with background and current examples provided.Table of ContentsChapter 1. Big Data Analytics in Healthcare; Kalaiselvi K and Thirumurthi Raja Chapter 2. A Big Data Analytics in Health Sector: Need, Opportunities, Challenges and Future Prospects; Anam and M. Israrul Haque Chapter 3. Use of Classification Algorithms in Healthcare; Hera Khan, Ayush Srivastav and Amit Kumar Mishra Chapter 4. Big Data Analytics in Excelling Health Care: Achievement and Challenges in India; Arindam Chakrabarty and Uday Sankar Das Chapter 5. Predictive Big Data Analytics in Healthcare; Shivinder Nijjer, Sahil Raj and Saurabh Kumar Chapter 6. Smart Nursery with Health Monitoring System through Integration of IoT and Machine Learning; Rashbir Singh, Prateek Singh and Latika Kharb Chapter 7. Computer-aided big healthcare data (BHD) analytics; Tawseef Shaikh and Rashid Ali Chapter 8. Intrusion Detection and Security System; Prerna Sharma and Deepali Kamthania Chapter 9. Decision making with BI in Healthcare domain; Bhawna Suri, Shweta Taneja and Hemanpreet Singh Kalsi Chapter 10. Assistance for Facial Palsy using Quantitative Technology; Gulpreet Kaur Chadha and Seema Rawat Chapter 11. Constructive Effect of Ranking Optimal features using Random Forest for Breast Cancer Diagnosis using Support Vector Machine and Naïve Bayes Classifiers; Deepa G and Senthil S Chapter 12. Intelligent Establishment of Correlation of TTH and Diabetes Mellitus on Subject’s Physical Characteristics: MMBD and ML Perspective in Healthcare; Parul Singhal and Rohit Rastogi Chapter 13. Machine Learning Model for Meal Classification and Assessing Nutrients value according to Weather Conditions; Madhulika Bhatia, Shubham Sharma, Madhurima Hooda, Narayan C. Debnath Chapter 14: Telehealth: Former, Today and Later; Madhulika Bhatia, Shubham Chaudhary, Madhurima Hooda, Bhuvanesh Unhelkar Chapter 15. Predictive Modelling in Health Care Data Analytics – A Sustainable Supervised Learning Technique; Suryakanthi Tangirala

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Book SynopsisInformation retrieval is a central and essential activity. It is indeed difficult to find a human activity that does not need to retrieve information in an environment which is often increasingly digital: moving and navigating, learning, having fun, communicating, informing, making a decision, etc. Most human activities are intimately linked to our ability to search quickly and effectively for relevant information, the stakes are sometimes extremely important: passing an exam, voting, finding a job, remaining autonomous, being socially connected, developing a critical spirit, or simply surviving. The author of this book presents a summary of work undertaken over several years relative to the behaviors and cognitive processes involved in information retrieval in digital environments. He presents several examples of theoretical models and studies to better understand the difficulties, behaviors and strategies of individuals searching for information in digital environments.Table of ContentsCHAPTER 1. INFORMATION RETRIEVAL IN DIGITAL ENVIRONMENTS: DEBATE AND SCIENTIFIC DIRECTIONS 1 1.1. Information retrieval, current and future challenges 1 1.2. What are we talking about? 3 1.3. Interaction and navigation at the heart of information retrieval 7 1.4. Why should we be interested in information retrieval? 9 1.4.1. Economy: maximize profitability and minimize risks 10 1.4.2. Information technology: mathematical concepts of the relevance of information 12 1.4.3. Robotics: improving movements and interactions 14 CHAPTER 2. CONCEPTUAL AND METHODOLOGICAL APPROACHES TO INFORMATION RETRIEVAL IN DIGITAL ENVIRONMENTS 19 2.1. The approaches of information sciences: the precursors 19 2.2. The Marchionini sequential iterative model 21 2.3. The holistic model of Kuhlthau 23 2.4. The first studies of psychology and cognitive ergonomics 26 2.5. The cyclic model of David, Song, Hayes and Fredin 31 2.6. The skills-centered model of Brand-Gruwel 33 2.7. Kitajima’s predictive model 36 2.8. The hyper-specialized model of Sharit, Hernandez, Czaja and Pirolli 39 2.9. The Landscape Model “diversion” by Dinet 42 CHAPTER 3. INFORMATION RETRIEVAL: PSYCHOERGONOMIC APPROACH 49 3.1. Introduction 49 3.2. Identifying difficulties in modifying interfaces 51 3.2.1. Hierarchical task analysis 52 3.2.2. Analysis of the end users’ behavior 55 3.2.3. Implications for the (re)design of interfaces 61 3.3. Anticipating the needs of users 63 3.3.1. “If we built it, they will come” 64 3.3.2. The analysis of users’ expectations and behaviors 65 3.3.3. Prospective ergonomics and technological innovation 70 3.3.4. Anticipating and understanding the needs of users: the method of staff made up of community experts 73 3.3.5. An example of application of the method of staff made up of community experts 76 3.4. The motor dimension 79 3.4.1. Motor ability and information retrieval in digital environments 79 3.4.2. Toward a lexicon of intuitive gestures 85 3.5. The social dimension and collaborative 88 3.5.1. From individual research to collaborative information retrieval 89 3.5.2. Benefits and limitations of collaborative information retrieval 90 3.6. Impact of emotional ties between collaborators 92 3.6.1. Ties between collaborators and impact on information retrieval 94 3.6.2. “RCI-Web”: software to assist information retrieval 97 3.7. The cultural dimension 102 3.7.1. About the importance of the home page 102 3.7.2. Culture and design of Websites’ home pages: an ergonomic inspection 105 3.7.3. Information retrieval culture and behavior navigation 107 3.8. The visual exploration strategies109 3.8.1. Impact of the typographical marking (bottom-up approach) 112 3.8.2. Impact of the mental model (top-down approach) 117 CONCLUSION 123 BIBLIOGRAPHY 125 INDEX 165

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Book SynopsisAcclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.Table of ContentsPREFACE xi Gérald KEMBELLEC, Ghislaine CHARTRON and Imad SALEH CHAPTER 1. GENERAL INTRODUCTION TO RECOMMENDER SYSTEMS 1 Ghislaine CHARTRON and Gérald KEMBELLEC 1.1. Putting it into perspective 1 1.2. An interdisciplinary subject 2 1.3. The fundamentals of algorithms 4 1.3.1. Collaborative filtering 4 1.3.2. Content filtering 7 1.3.3. Hybrid methods 9 1.3.4. Conclusion on historical recommendation models 11 1.4. Content offers and recommender systems 11 1.4.1. Culture and recommender systems 11 1.4.2. Recommender systems and the e-commerce of content 16 1.4.3. The behavior of users 18 1.5. Current issues 19 1.6. Bibliography 19 CHAPTER 2. UNDERSTANDING USERS’ EXPECTATIONS FOR RECOMMENDER SYSTEMS: THE CASE OF SOCIAL MEDIA 25 Jean-Claude DOMENGET and Alexandre COUTANT 2.1. Introduction: the omnipresence of recommender systems 25 2.2. The social approach to prescription 27 2.2.1. The theory of the prescription and online interactions 27 2.2.2. Conditions for recognition of the prescription 29 2.2.3. The specificities of social media 30 2.3. Users who do not focus on the prescriptions of platforms 31 2.3.1. Facebook: the link, the type of activity and the context 32 2.3.2. Twitter: prescription between peers and explanation of prescription 38 2.3.3. Conditions for the recognition of a prescription: announcement and enunciation 44 2.4. A guide for considering recommender systems adapted to different forms of social media 45 2.5. Conclusion 48 2.6. Bibliography 49 CHAPTER 3. RECOMMENDER SYSTEMS AND SOCIAL NETWORKS: WHAT ARE THE IMPLICATIONS FOR DIGITAL MARKETING? 53 Maria MERCANTI-GUÉRIN 3.1. Social recommendations: an ancient practice revived by the digital age 54 3.1.1. Recommendations: a difficult management for brands 55 3.1.2. Internet recommendations: social presence and personalized recommendations 55 3.2. Social recommendations: how are they used for e-commerce? 58 3.2.1. Efficiency of recommender systems with regard to the performance of e-commerce websites 58 3.2.2. Recommender systems used by social networks: from e-commerce to social commerce 59 3.3. Conclusion 66 3.4. Bibliography 68 CHAPTER 4. RECOMMENDER SYSTEMS AND DIVERSITY: TAKING ADVANTAGE OF THE LONG TAIL AND THE DIVERSITY OF RECOMMENDATION LISTS 71 Muriel FOULONNEAU, Valentin GROUÈS, Yannick NAUDET and Max CHEVALIER 4.1. The stakes associated with diversity within recommender systems 72 4.1.1. Individual diversity or the individual perception of diversity 73 4.1.2. The stakes and impacts of aggregate diversity 74 4.2. Recommendation algorithms and diversity: trends, evaluation and optimization 77 4.2.1. The tendency for recommendation algorithms to focus on the head 78 4.2.2. The evaluation of diversity in recommender systems 80 4.2.3. Recommendation algorithms which favor individual diversity 81 4.2.4. Recommendation algorithms which favor aggregate diversity 81 4.2.5. The shift toward user-centered diversity approaches 82 4.3. Conclusion and new directions 85 4.4. Bibliography 87 CHAPTER 5. ISONTRE: INTELLIGENT TRANSFORMER OF SOCIAL NETWORKS INTO A RECOMMENDATION ENGINE ENVIRONMENT 93 Rana CHAMSI ABU QUBA, Salima HASSAS, Usama FAYYAD, Hammam CHAMSI and Christine GERTOSIO 5.1. Summary 93 5.2. Introduction 94 5.3. Latest developments, definition and history 97 5.3.1. Collaborative filtering techniques 97 5.3.2. General use social networks: what do they contain? 97 5.3.3. Social recommendation 99 5.3.4. The recommendation of concepts 100 5.4. iSoNTRE 101 5.4.1. iSoNTRE: transformer of social networks 102 5.4.2. iSoNTRE: the core of recommendation 107 5.5. Experiments 110 5.5.1. The preparation of data 110 5.5.2. Testing methodology 110 5.5.3. The creation of avatars 111 5.5.4. Results 112 5.5.5. Discussion 113 5.6. Conclusion 114 5.7. Bibliography 115 CHAPTER 6. A TWO-LEVEL RECOMMENDATION APPROACH FOR DOCUMENT SEARCH 119 Manel HMIMIDA and Rushed KANAWATI 6.1. Introduction 119 6.2. Tag recommendation: a brief state of the art 120 6.3. The hypertagging system 122 6.3.1. Metadata 122 6.3.2. Architecture 123 6.4. Recommendation approach 124 6.4.1. Presentation 124 6.4.2. Recommendation algorithm 126 6.5. Evaluation 127 6.5.1. Generation of facets 127 6.5.2. Generation of association rules 129 6.5.3. Evaluation of recommendation rules 130 6.6. Conclusion 131 6.7. Bibliography 132 CHAPTER 7. COMBINING CONFIGURATION AND RECOMMENDATION TO ENABLE AN INTERACTIVE GUIDANCE OF PRODUCT LINE CONFIGURATION 135 Raouia TRIKI , Raúl MAZO and Camille SALINESI 7.1. Introduction 135 7.2. Context 137 7.2.1. Configuration 137 7.2.2. Recommendation 139 7.2.3. Obstacles and challenges of interactive PL configuration 141 7.3. Overview of the proposed approach 142 7.4. Preliminary evaluation 148 7.5. Discussion and related work 148 7.5.1. Recommendation techniques 148 7.6. Conclusion and future work 151 7.7. Bibliography 151 CHAPTER 8. SEMIO-COGNITIVE SPACES: THE FRONTIER OF RECOMMENDER SYSTEMS 157 Hakim HACHOUR, Samuel SZONIECKY and Safia ABOUAD 8.1. Introduction 157 8.2. Latest developments: finalized activities, recommender systems and the relevance of information 159 8.2.1. Cognitive dynamics of finalized activities 159 8.2.2. The foundations of recommender systems 161 8.2.3. What information relevance? 166 8.3. Observable interests for decision theory: a combination of content-based, collaboration based and knowledge-based recommendations 169 8.3.1. Methodology: meta-analysis and modeling of the process 169 8.3.2. Analysis and modeling of a macro-process for responding to a call for R&D projects 171 8.3.3. Analysis and model of a socio-organizational tool for the management of customer complaints 173 8.4. Discussion and conclusions 177 8.4.1. Discussion: the performance of the filtering methods and semio-cognitive criteria for relevance 177 8.5. Conclusions: recommender systems linked to finalized activities 181 8.5.1. The localization of activities and geographical information systems: a new kind of data 182 8.5.2. Transparency of the use of personal data, data protection and ownership 183 8.6. Acknowledgments 185 8.7. Bibliography 185 CHAPTER 9. THE FRENCH-SPEAKING LITERARY PRESCRIPTION MARKET IN NETWORKS 191 Louis WIART 9.1. Introduction 191 9.2. The economy of prescription 193 9.2.1. The notion of prescription 193 9.2.2. From the advisors market to the prescription market 194 9.3. Methodology 196 9.4. The competitive structure of the market of online social networks of readers 197 9.4.1. Pure player networks and the audience strategy 199 9.4.2. Amateur networks and the survival strategy 201 9.4.3. Backed networks and the hybridization strategy 202 9.5. The organization of prescription 204 9.5.1. Social prescription 205 9.5.2. Editorial prescription 206 9.5.3. Algorithmic prescription 207 9.6. Conclusion: what legitimacy for literary prescription? 208 9.7. Appendix: list of interviews undertaken 210 9.8. Bibliography 210 CHAPTER 10. PRESENTATION OF OFFERED SERVICES: BABELIO, A RECOMMENDATION ENGINE DEDICATED TO BOOKS 213 Vassil STEFANOV, Guillaume TEISSEIRE and Pierre FRÉMAUX 10.1. Introduction 213 10.2. The problem of qualitative pertinence 216 10.3. The problem of quantitative pertinence 217 10.4. Balancing recall and precision 217 10.5. The issue of sparse data 218 10.6. Performance and scalability 218 10.7. A few issues specific to books 219 CHAPTER 11. PRESENTATION OF THE OFFER OF SERVICES: NOMAO, RECOMMENDER SYSTEMS AND INFORMATION SEARCH 221 Estelle DELPECH, Laurent CANDILLIER and Étienne CHAI 11.1. Introduction: the actors of Internet recommendation 221 11.2. Approaches to recommendation 222 11.3. Nomao: a local outlets search and recommendation engine 223 11.3.1. Popularity score 223 11.3.2. Affinity score 224 11.3.3. Social recommendation 225 11.4. Prospects: the move toward interactive recommender systems 225 11.5. Appendix 226 LIST OF AUTHORS 227 INDEX 231

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Book SynopsisEnterprises and organizations of any kind embedded in today's economic environment are deeply dependent on their ability to take part in collaborations. Consequently, it is strongly required for them to get actively involved for their own benefit in emerging, potentially opportunistic collaborative enterprise networks. The concept of “interoperability” has been defined by INTEROP-VLab as “The ability of an enterprise system or application to interact with others at a low cost in a flexible approach”. Consequently, interoperability of organizations appears as a major issue to succeed in building on the fly emerging enterprise networks. The International Conference on Interoperability for Enterprise Systems and Applications (I-ESA 2014) was held under the motto “interoperability for agility, resilience and plasticity of collaborations” on March 26-28, 2014 and organized by the Ecole des Mines d’Albi-Carmaux, France on behalf of the European Laboratory for Enterprise Interoperability (INTEROP-VLab). On March 24-25, co-located with the conference eight workshops and one doctoral symposium were held in four tracks complementing the program of the I-ESA’14 conference. The workshops and the doctoral symposium address areas of greatest current activity focusing on active discussions among the leading researchers in the area of Enterprise Interoperability. This part of the conference helps the community to operate effectively, building co-operative and supportive international links as well as providing new knowledge of on-going research to practitioners. The workshops and doctoral symposium aimed at exploiting new issues, challenges and solutions for Enterprise Interoperability (EI) and associated domains of innovation such as Smart Industry, Internet-Of-Things, Factories of the Future, EI Applications and Standardisation. These proceedings include the short papers from the I-ESA’14 workshops and the doctoral symposium. The book is split up into 9 sections, one for each workshop and one for the doctoral symposium. All sections were organized following four tracks: (1) EI and Future Internet / Factory of the Future; (2) EI Application Domains and IT; (3) EI Standards; (4) EI Doctoral Symposium. For each section, a workshop report is provided summarizing the content and the issues discussed during the sessions. The goal of the first track was to offer a discussion opportunity on interoperability issues regarding the use of Internet of Things on manufacturing environment (Workshops 1 and 3) on one hand, and regarding the potential of innovation derived from the use of digital methods, architectures and services such as Smart Networks (Workshops 2 and 4) on the other hand. The second track focused on particular application domains that are looking for innovative solutions to support their strong collaborative needs. Thus, the track developed one workshop on the use of EI solution for Future City-Logistics (Workshop 5) and one on the use of EI solutions for Crisis / Disaster Management (Workshop 6). The third track studied the recent developments in EI standardization. Two workshops were dedicated to this issue. The first one has proposed to focus on the management of standardization (Workshop 8) and the second one has chosen to work on the new knowledge on standardization developments in the manufacturing service domain (Workshop 9). The last track, the doctoral symposium presented research results from selected dissertations. The session discussed EI knowledge issues, notably in terms of gathering through social networks or Internet of Things and of exploitation through innovative decision support systems.Table of ContentsPreface xiM. LAURAS, M. ZELM, B. ARCHIMÈDE, F. BÉNABEN, G. DOUMEINGTS Workshop 1. IoT Interoperability for Manufacturing: Challenges and Experiences 1 ReportD. ROTONDI 2 Smart Industry Services in Times of Internet of Things and Cloud Computing 5M. SERRANO, P. DIMITROPOULOS Designing and Executing Interoperable IoT Manufacturing Systems 15U. KANNENGIESSER, G. WEICHHART Internet of Things Research on Semantic Interoperability to Address Manufacturing Challenges 21P. COUSIN, M. SERRANO, J. SOLDATOS Manufacturing Integration Challenges: Top-Down Interoperability and Bottom-Up Comprehensiveness Towards a Global Information Backbone for Smart Factory 31V.K. NGUYEN An Improved Decision Support System in Factory Shop-Floor through an IoT Approach 37P. PETRALI Leveraging IoT Interoperability for Enhanced Business Process in Smart, Digital and Virtual Factories 43J. SOLA, A. GONZALEZ, O. LAZARO Workshop 2. Future Internet Methods, Architectures and Services for Digital Business Innovation in Manufacturing, Health and Logistics Enterprises 49 Report 50S. GUSMEROLI, G. DOUMEINGTS Future Internet Technologies and Platforms to Support Smart, Digital and Virtual and Business Processes for Manufacturing 53J. SOLA, A. GONZALEZ, O. LAZARO Delivering Care in a Future Internet59 C. THUEMMLER, T. JELL FITMAN Verification and Validation Method: Business Performance Indicators and Technical Indicators 64G. DOUMEINGTS, B. CARSALADE, M. RAVELOMANANTSOA, F. LAMPATHAKI, P. KOKKINAKOS, D. PANOPOULOS Validation and Quality in FI-PPP e-Health Use Case, FI-STAR Project 71P. COUSIN, S. FRICKER, D. FEHLMY, F. LE GALL, M. FIEDLER Workshop 3. ICT Services and Interoperability for Manufacturing 81 Report82K. POPPLEWELL Intelligent Systems Configuration Services for Flexible Dynamic Global Production Networks 85R.I.M. YOUNG, K. POPPLEWELL, F.-W. JAEKEL, B. OTTO, G. BHULLAR Binding Together Heterogeneous Future Internet Services in Manufacturing Workplaces 91M. SESANA, S. GUSMEROLI, R. SANGUINI Holistic, Scalable and Semantic Approach at Interoperable Virtual Factories 95G. PAVLOV, V. MANAFOV, I. PAVLOVA, A. MANAFOV Predictive Industrial Maintenance: A Collaborative Approach 101F. FERREIRA, A. SHAMSUZZOHA, A. AZEVEDO, P. HELO On Optimizing Collaborative Manufacturing Processes in Virtual Factories 108D. SCHULLER, R. HANS, S. ZÖLLER, R. STEINMETZ Modelling Interoperability-Related, Economic and Efficiency Benefits in Dynamic Manufacturing Networks through Cognitive Mapping 115O.I. MARKAKI, S. KOUSSOURIS, P. KOKKINAKOS, D. PANOPOULOS, D. ASKOUNIS Cloud-Based Interoperability for Dynamic Manufacturing Networks 122D. STOCK, A. BILDSTEIN A smart Mediator to Integrate Dynamic Networked Enterprises 128C. DIOP, A. KAMOUN, E. MEZGHANI, M. ZOUARI, E. EXPOSITO Workshop 4. SmartNets – Collaborative Development and Production of Knowledge-Intensive Products and Services 135 Report 136A. LAU The Industrial Model of Smart Networks for SME Collaboration: Implementation and Success Stories 139A. LAU, M. TILEBEIN, T. FISCHER Towards a Conceptual Model of the Resource Base for Hyperlinking in Innovation Networks 146S.-V. REHM, S. GROSS Enhanced Incubators: Fostering Collaboration, Growth and Innovation 152T.J. MARLOWE, V. KIROVA, M. MOHTASHAMI Application of the SmartNets Methodology in Manufacturing Service Ecosystems 158M. HIRSCH, D. OPRESNIK, H. MATHEIS Application of a Domain-Specific Language to Support the User-Oriented Definition of Visualizations in the Context of Collaborative Product Development 164T. RESCHENHOFER, I. MONAHOV, F. MATTHES Workshop 5. Collaboration Issues for City-Logistics 171 Report – G. MACE-RAMETE, J. GONZALEZ-FELIU 172 Simulation-Based Analysis of Urban Freight Transport with Stochastic Features 175N. HERAZO-PADILLA, J.R. MONTOYA-TORRES, S. NIETO-ISAZA, L. RAMIREZ POLO, L. CASTRO, D. RAMÍREZ, C.L. QUINTERO-ARAÚJO Impacts of Urban Logistics on Traffic Flow Dynamics 181N. CHIABAUT, J.-M. SIGAUD, G. MARQUES, J. GONZALEZ-FELIU A Basic Collaborative City Logistics’ Solution: The Urban Consolidation Centre 188L. FAURE, B. MONTREUIL, G. MARQUÈS, P. BURLAT VRP Algorithms for Decision Support Systems to Evaluate Collaborative Urban Freight Transport Systems 196J. GONZALEZ-FELIU, J.-M. SALANOVA GRAU The Last Food Mile Concept as a City Logistics Solution for Perishable Products: The Case of Parma's Food Urban Distribution Center 202E. MORGANTI, J. GONZALEZ-FELIU Supporting Decision for Road Crisis Management through an Agile and Collaborative Information System 208G. MACÉ-RAMÈTE, F. BÉNABEN, M. LAURAS, J. LAMOTHE Workshop 6. Applications of Advanced Technologies in the Context of Disaster Relief and Crisis Management 213 Report – A. CHARLES214 Enhancing the Emergency Response Using an Event-Driven System 216A.-M. BARTHE-DELANOË, F. BÉNABEN, M. LAURAS, S. TRUPTIL Designing Decision Support Systems for Humanitarian Organisations: Requirements and Issues 222K. SAKSRISATHAPORN, A. CHARLES, A. BOURAS From Global to Local Disaster Resilience: The Case of Typhoon Haiyan 228T. COMES, B. VAN DE WALLE Workshop 8. Corporate Standardisation Management 235 Report – K. JAKOBS 236 Lack of Openness as a Potential Failure in Standardisation Management: Lessons Learnt from Setbacks in European Learning Technology Standardisation 238T. HOEL The Individual in Standard Setting: Selection, Training, Motivation in the Public Sector 244G. CANARSLAN A Framework for the Management of Intra-Organizational Security Process Standardization 250C. SILLABER, M. BRUNNER, R. BREU Standards Roles in Hacklin's Strategic Model: Cases in the Space Sector 256K. BENMEZIANE, A. MIONE Standardization Management and Decision-Making: The Case of a Large Swedish Automotive Manufacturer 261A. FOUKAKI Some Factors Influencing Corporate ICT Standardisation Management 267K. JAKOBS Workshop 9. Standardisation Developments for Enterprise Interoperability and the Manufacturing Service Domain 273 Report – M. ZELM, D. CHEN 274 Towards Standardisation in Manufacturing Service Engineering of Ecosystem 277M. ZELM, G. DOUMEINGTS Framework for Manufacturing Servitization: Potentials for standardization 283D. CHEN, S. GUSMEROLI How Can Existing Standards Support Service Life Cycle Management 290M. FREITAG, M. HIRSCH, J. NEUHÜTTLER An Approach to Interoperability Testing to Speed up the Adoption of Standards 295A. BRUTTI, P. DE SABBATA, N. GESSA A Common Vocabulary to Express Standardization Features: Towards the Interoperability of Industrial Data Standards 301A.-F. CUTTING-DECELLE, G.-I. MAGNAN, C. MOUTON, R.I.M. YOUNG An Info*Engine-Based Architecture to Support Interoperability with Windchill System 308M. ANIS DHUIEB, F. BELKADI, F. LAROCHE, A. BERNARD Doctoral Symposium 315 Report – B. ARCHIMÈDE, J. LAMOTHE 316 Build Enterprise Relationship Network to Support Collaborative Business 318L. WANG, S. LIU, L. WU, L. PAN, X. MENG Analysing Internet of Things to Feed Internet of Knowledge: Support Decision-Making in Crisis Context 325A. SIRKO, S. TRUPTIL, A.-M. BARTHE- DELANOË, F. BÉNABEN On the Interoperability in Marine Pollution Disaster Management 331V. NICOLESCU, M. CARAIVAN, G. SOLOMON, V. CIUPINA A Framework for Characterizing Collaborative Networks of Organizations 337A. MONTARNAL, X. FERNANDEZ, J. LAMOTHE, F. GALASSO, C. THIERRY, F. BÉNABEN, M. LAURAS Index of Authors 343

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Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis Appendix A. Bayesian Statistics Appendix B. Expectation-Maximization Appendix C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies

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Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis App. A. Bayesian Statistics App. B. Expectation-Maximization App. C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies

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Book SynopsisUsing Android as a reference, this book teaches the development of mobile apps designed to be responsive, trustworthy and robust, and optimized for maintainability. As the share of mission-critical mobile apps continues to increase in the ever-expanding mobile app ecosystem, it has become imperative that processes and procedures to assure their reliance are developed and included in the software life cycle at opportune times. Memory, CPU, battery life and screen size limitations of smartphones coupled with volatility associated with mobile environments underlines that the quality assurance strategies that proved to be successful for desktop applications may no longer be effective in mobile apps. To that effect, this book lays a foundation upon which quality assurance processes and procedures for mobile apps could be devised. This foundation is composed of analytical models, experimental test-beds and software solutions. Analytical models proposed in the literature to predict software quality are studied and adapted for mobile apps. The efficacy of these analytical models in prejudging the operations of mobile apps under design and development is evaluated. A comprehensive test suite is presented that empirically assesses a mobile app’s compliance to its quality expectations. Test procedures to measure quality attributes such as maintainability, usability, performance, scalability, reliability, availability and security, are detailed. Utilization of test tools provided in Android Studio as well as third-party vendors in constructing the corresponding test-beds is highlighted. An in-depth exploration of utilities, services and frameworks available on Android is conducted, and the results of their parametrization observed through experimentation to construct quality assurance solutions are presented. Experimental development of some example mobile apps is conducted to gauge adoption of process models and determine favorable opportunities for integrating the quality assurance processes and procedures in the mobile app life cycle. The role of automation in testing, integration, deployment and configuration management is demonstrated to offset cost overheads of integrating quality assurance process in the life cycle of mobile apps. Table of ContentsAbbreviations and Acronyms List of Figures List of Tables Listing 1 Software Life Cycle 1.1 Process Models 1.2 Functional Specifications 1.2.1 User Stories 1.2.2 UML Use Case Diagrams 1.2.3 Software Requirements Specifications 1.3 Non-Functional Requirements 1.4 Test Driven Development 1.4.1 Acceptance Tests 1.4.2 Unit Tests 1.5 Continuous Integration and Delivery 1.5.1 Software Configuration Management 1.5.2 Continuous Integration and Delivery Summary EXERCISES REFERENCES 2 Development Fundamentals 2.1 Graphical User Interface 2.1.1 GUI Objects and Layouts 2.1.2 Event Handling 2.1.3 Redirection 2.2 Data Storage 2.2.1 Key-value Pairs 2.2.2 Files 2.2.3 Database Systems 2.2.4 Personal Data Storage 2.3 Data Connectivity 2.3.1 Web Access 2.3.2 Short Message Service 2.4 Concurrency 2.4.1 Threads and Asynchronous Tasks 2.4.2 Processes 2.5 Location and Sensor APIs Summary EXERCISES REFERENCES 3 Software Quality Assessment 3.1 Functional Requirements Testing 3.1.1 Equivalence Class Partitioning 3.1.2 Boundary Value Analysis 3.1.3 Domain Test Design 3.2 Maintainability 3.2.1 Sub-Characteristics 3.2.2 Maintainability Measures 3.3 Usability and Accessibility 3.3.1 Models 3.3.2 Evaluation 3.4 Performance Testing 3.4.1 Latency Measurement 3.4.2 GUI Performance 3.4.3 Memory Usage 3.4.4 Network Usage 3.4.5 Battery Usage 3.5 Scalability Testing 3.5.1 Scalability Models 3.5.2 Load Test Design 3.6 Reliability Testing 3.6.1 Growth Models 3.6.2 Fault Injection 3.6.3 Operational Profile 3.6.4 Reliability Test Design 3.7 Availability 3.7.1 Availability Models 3.7.2 Stress Testing 3.8 Safety 3.8.1 FMEA 3.8.2 FTA 3.9 Security 3.9.1 Vulnerabilities and Threat Analysis 3.9.2 Security Testing 3.10 Static Code Analysis Summary EXERCISES REFERENCES 151 4 Maintainability and Multi-Platform Development 4.1 Software Patterns 4.1.1 Programming Paradigms 4.1.2 Design Patterns 4.1.3 Architecture Patterns 4.2 Design Description 4.2.1 Structural 4.2.2 Behavioral 4.3 Multi-Platform Development 4.3.1 Native Development 4.3.2 Hybrid 4.3.3 Cross-Platform Development Summary EXERCISES REFERENCES 5 User Interaction Optimization 5.1 Multimodality 5.1.1 Touch Gestures 5.1.2 Motion Gestures 5.1.3 Verbal Gestures 5.1.4 Visual Gestures 5.1.5 Accessibility Frameworks 5.2 Navigation Controls 5.3 Dashboards 5.4 Custom GUI 5.5 Animated GUI Summary EXERCISES REFERENCES 6 Performance Acceleration 6.1 Data Compression 6.1.1 Lossless Compression 6.1.2 Lossy Compression 6.2 Data I/O Optimization 6.2.1 File System I/O 6.2.2 Network I/O 6.3 Rendering Pipelines 6.3.1 Animation Rendering 6.3.2 Video Rendering 6.3.3 Augmented Reality 6.3.4 Hardware Acceleration 6.4 Parallel Programming 6.4.1 Thread Priority 6.4.2 Data Parallel Computation Summary EXERCISES REFERENCES 7 Scalability Provisioning 7.1 Scalable Media Transport 7.2 Scalable Local Storage 7.2.1 Data Models 7.2.2 Data Structures and Query Plan 7.2.3 Location Queries 7.3 Scalable Design Patterns 7.3.1 Data Cache 7.3.2 Event Notifications 7.3.3 Task Scheduling 7.4 GUI Scalability Summary EXERCISES REFERENCES 8 Reliability Assurance 8.1 Thread Safe Patterns 8.1.1 Serializing GUI Updates 8.1.2 Serializing Shared Memory Access 8.1.3 Thread Synchronization 8.2 Memory Leaks 8.3 Reliable Persistent Storage 8.3.1 Isolation and Consistency 8.3.2 Atomicity and Durability 8.3.3 Sharded Persistent Storage 8.4 Data Validation 8.4.1 Input Validation 8.4.2 Integrity Constraints 8.5 Stateful Data Transport Summary EXERCISES REFERENCES 9 Availability and Fault-Tolerance 9.1 Availability Primitives 9.1.1 Design Diversity 9.1.2 Broadcast Primitives 9.2 Critical Communication Availability 9.2.1 Network Fault Tolerance 9.2.2 Design Diverse Emergency Communication Architecture 9.3 Sensor Fusion and Redundancy 9.4 Data Availability 9.4.1 Data Synchronization 9.4.2 Data Sharing 9.5 Battery Power Saving Summary EXERCISES REFERENCES 10 Security and Trust 10.1 Cryptographic Primitives 10.1.1 Symmetric Cryptography 10.1.2 Asymmetric Cryptography 10.1.3 Message Digest 10.1.4 Message Authentication Codes 10.1.5 Digital Signatures 10.2 Secure Web Access 10.2.1 User Authentication 10.2.2 Authentication Delegation and Single Sign On 10.2.3 Access and Authorization Delegation 10.2.4 Peer-Authentication and Confidentiality 10.3 Secure Network Access 10.3.1 Transport Layer Security 10.3.2 Layer 3 Security 10.3.3 Layer 2 Security 10.4 Secure System Access 10.4.1 Mobile Application Authenticity 10.4.2 Securing Inter-Application Communication 10.4.3 Permissions and Access Control Summary EXERCISES REFERENCES Appendix A Appendix B B.1 Compile and Deploy a Servlet B.2 Compile and Deploy a Web Socket Hub B.3 Configure Tomcat to Enable SSL B.4 Install and Configure Jenkins B.5 Install Metrics Reloaded Index

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Book SynopsisThe vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowledge that can present a tremendous advantage to the Artificial Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as an accessible but rigorous overview of this body of work. The book presents interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.Table of Contents1. What is a knowledge graph?.- 2. Information Extraction.- 3. Entity Resolution.- 4. Advanced Topic: Knowledge Graph Completion.- 5. Ecosystems

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Book SynopsisThis book contains selected papers presented at the 13th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Vienna, Austria, in August 2018. The 10 full papers included in this volume were carefully reviewed and selected from 27 submissions. Also included are reviewed papers summarizing the results of workshops and tutorials that were held at the Summer School as well as papers contributed by several of the invited speakers. The papers combine interdisciplinary approaches to bring together a host of perspectives: technical, legal, regulatory, socio-economic, social, societal, political, ethical, anthropological, philosophical, historical, and psychological. Table of ContentsA Causal Bayesian Networks Viewpoint on Fairness.- Sharing is caring, a boundary object approach to mapping and discussing personal data processing.- Who You Gonna Call When There's Something Wrong in Your Processing? Risk Assessment and Data Breach Notications in Practice.- Design and Security Assessment of Usable Multi-Factor Authentication and Single Sign-On Solutions for Mobile Applications: A Workshop Experience Report.- Towards Empowering the Human for Privacy Online.- Trust and Distrust: On Sense and Nonsense in Big Data.- GDPR transparency requirements and data privacy vocabularies.- Glycos: the basis for a peer-to-peer, private online social network.- GDPR and the Concept of Risk: The Role of risk, the Scope of risk and the technology involved.- Privacy Patterns for Pseudonymity.- Implementing GDPR in the Charity Sector: A Case Study.- Me and My Robot! Sharing Information with a New Friend.- chownIoT: Enhancing IoT Privacy by Automated Handling of Ownership Change.- Is Privacy Controllable?.- Assessing Theories for Research on Personal Data Transparency.- Data Protection by Design for cross-border electronic identication: does the eIDAS Interoperability Framework need to be modernised?.- Risk proling by law enforcement agencies in the Big Data era: Is there a need for transparency?

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Book SynopsisThis book constitutes the refereed proceedings of the 8th EAI International Conference on Game Theory for Networks, GameNets 2019, held in Paris, France, in April 2019. The 8 full and 3 short papers presented were carefully reviewed and selected from 17 submissions. They are organized in the following topical sections: Game Theory for Wireless Networks; Games for Economy and Resource Allocation; and Game Theory for Social Networks.Table of ContentsGame Theory for Wireless Networks.- Games for Economy and Resource Allocation.- Game Theory for Social Networks.

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Book SynopsisThis book describes methods and tools that empower information providers to build and maintain knowledge graphs, including those for manual, semi-automatic, and automatic construction; implementation; and validation and verification of semantic annotations and their integration into knowledge graphs. It also presents lifecycle-based approaches for semi-automatic and automatic curation of these graphs, such as approaches for assessment, error correction, and enrichment of knowledge graphs with other static and dynamic resources.Chapter 1 defines knowledge graphs, focusing on the impact of various approaches rather than mathematical precision. Chapter 2 details how knowledge graphs are built, implemented, maintained, and deployed. Chapter 3 then introduces relevant application layers that can be built on top of such knowledge graphs, and explains how inference can be used to define views on such graphs, making it a useful resource for open and service-oriented dialog systems. Chapter 4 discusses applications of knowledge graph technologies for e-tourism and use cases for other verticals. Lastly, Chapter 5 provides a summary and sketches directions for future work. The additional appendix introduces an abstract syntax and semantics for domain specifications that are used to adapt schema.org to specific domains and tasks.To illustrate the practical use of the approaches presented, the book discusses several pilots with a focus on conversational interfaces, describing how to exploit knowledge graphs for e-marketing and e-commerce. It is intended for advanced professionals and researchers requiring a brief introduction to knowledge graphs and their implementation. Table of ContentsIntroduction: What is a Knowledge Graph?.- How to build a Knowledge Graph.- How to use a Knowledge Graph.- Why we need Knowledge Graphs: Applications.- Conclusions.- References.- Appendix.- Index.

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Book SynopsisThis book constitutes the thoroughly refereed proceedings of the 16th Italian Research Conference on Digital Libraries, IRCDL 2020, held in Bari, Italy, in January 2020.The 12 full papers and 6 short papers presented were carefully selected from 26 submissions. The papers are organized in topical sections on information retrieval, bid data and data science in DL; cultural heritage; open science. Table of ContentsInformation Retrieval.- Bid Data and Data Science in DL.- Cultural Heritage.- Open Science.

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Book SynopsisThis volume contains a collection of studies in the areas of complexity theory and property testing. The 21 pieces of scientific work included were conducted at different times, mostly during the last decade. Although most of these works have been cited in the literature, none of them was formally published before. Within complexity theory the topics include constant-depth Boolean circuits, explicit construction of expander graphs, interactive proof systems, monotone formulae for majority, probabilistically checkable proofs (PCPs), pseudorandomness, worst-case to average-case reductions, and zero-knowledge proofs.Within property testing the topics include distribution testing, linearity testing, lower bounds on the query complexity (of property testing), testing graph properties, and tolerant testing. A common theme in this collection is the interplay between randomness and computation.Table of ContentsA Probabilistic Error-Correcting Scheme that Provides Partial Secrecy.- Bridging a Small Gap in the Gap Ampli cation of Assignment Testers.- On (Valiant's) Polynomial-Size Monotone Formula for Majority.- Two Comments on Targeted Canonical Derandomizers.- On the Effect of the Proximity Parameter on Property Testers.- On the Size of Depth-Three Boolean Circuits for Computing Multilinear Functions.- On the Communication Complexity Methodology for Proving Lower Bounds on the Query Complexity of Property Testing.- Super-Perfect Zero-Knowledge Proofs.- On the Relation between the Relative Earth Mover Distance and the Variation Distance (an exposition).- The Uniform Distribution is Complete with respect to Testing Identity to a Fixed Distribution.- A Note on Tolerant Testing with One-Sided Error.- On Emulating Interactive Proofs with Public Coins.- Reducing Testing Affine Spaces to Testing Linearity of Functions.- Deconstructing 1-Local Expanders.- Worst-case to Average-case Reductions for Subclasses of P.- On the Optimal Analysis of the Collision Probability Tester (an exposition).- On Constant-Depth Canonical Boolean Circuits for Computing Multilinear Functions.- Constant-Round Interactive Proof Systems for AC0[2] and NC1.- Flexible Models for Testing Graph Properties.- Pseudo-Mixing Time of Random Walks.- On Constructing Expanders for any Number of Vertices.

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Book SynopsisThis book constitutes the refereed proceedings of the 8th IFIP WG 2.14 European Conference on Service-Oriented and Cloud Computing, ESOCC 2020, held in Heraklion, Crete, Greece, in September 2020. The 6 full and 8 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The main event mapped to the main research track which focused on the presentation of cutting-edge research in both the service-oriented and cloud computing areas. In conjunction, an industrial track was also held attempting to bring together academia and industry through showcasing the application of service-oriented and cloud computing research, especially in the form of case studies, in the industry.The chapters ‘Identification of Comparison Key Elements and their Relationships for Cloud Service Selection’ and ‘Technology-Agnostic Declarative Deployment Automation of Cloud Applications’ are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Table of ContentsFormal Methods.- Testing conformance in multi-component enterprise application management.- Formalizing Event-Driven Behavior of Serverless Applications.- Probabilistic Verification of Outsourced Computation Based on Novel Reversible PUFs.- Cloud Service and Platform Selection.- Multiplayer game backends: A Comparison of commodity cloud-based approaches.- Are Cloud Platforms Ready for Multi-Cloud?.- Identification of Comparison Key Elements and their Relationships for Cloud Service Selection.- Deployment and Workflows.- Deployable Self-Contained Workflow Models.- Technology-Agnostic Declarative Deployment Automation of Cloud Applications.- Blockchain-Based Healthcare Workflows in Federated Hospital Clouds.- Monitoring.- Monitoring Behavioral Compliance with Architectural Patterns based on Complex Event Processing.- Towards Real-Time Monitoring of Data Centers using Edge Computing.- Modeling Users' Performance: Predictive Analytics in an IoT Cloud Monitoring System.- Data Distribution and Analytics.- Multi-Source Distributed System Data for AI-powered Analytics.- Blockchain- and IPFS-based Data Distribution for the Internet of Things.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the First International Conference on Society with Future: Smart and Liveable Cities, SC4Life 2019, which took place in Braga, Portugal, in December 2019. The 13 revised full papers were carefully reviewed and selected from 19 submissions. The conference has brought researchers, developers, and practitioners who are leveraging and develoing new knowledge on the topic of smart cities, offering more efficiency to main infrastructures, utilities and services, creating a sustainable urban environment that improves the quality of life for its citizens and enhances economic development.Table of ContentsSustainable road infrastructures using smart materials, NDT, and FEM-based crack prediction.- Quantifying the carbon dioxide emissions resulting from awareness-raising actions of sustainable mobility.- Leak Detection in Water Distribution Networks via Pressure Analysis using a Machine Learning Ensemble.- Solutions for Improving the Energy Efficiency of Buildings Refurbishment Image recognition to improve positioning in smart urban environments.- An Hybrid Novel Layered Architecture and Case Study : IoT for Smart Agriculture and Smart LiveStock.- Agrilogistics - A Genetic Programming Based Approach.- Real World Third-Person with Multiple Point-of-Views for Immersive Mixed Reality.- Internet of Things for Enhanced Smart Cities: A Review, Roadmap and Case Study on Air Quality Sensing.- Smart pedestrian network: an integrated conceptual model for improving walkability.- Building future societies? A brief analysis of Braga’s School Bus project.- City rankings and the citizens: exposing representational and participatory gaps.- Mobility time style: For an integrated view of time and mobilities in societies with a future.

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Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic.The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity; demo and position papers; and doctoral symposium.Table of ContentsScalable Similarity Search.- Accelerating Metric Filtering by Improving Bounds on Estimated Distances.- Differentially Private Sketches for Jaccard Similarity Estimation.- Pivot Selection for Narrow Sketches by Optimization Algorithms.- mmLSH: A Practical and Efficient Technique for Processing Approximate Nearest Neighbor Queries on Multimedia Data.- Parallelizing Filter-Verification based Exact Set Similarity Joins on Multicores.- Similarity Search with Tensor Core Units.- On the Problem of p1 in Locality-Sensitive Hashing.- Similarity Measures, Search, and Indexing.- Confirmation Sampling for Exact Nearest Neighbor Search.- Optimal Metric Search Is Equivalent to the Minimum Dominating Set Problem.- Metrics and Ambits and Sprawls, Oh My: Another Tutorial on Metric Indexing.- Some branches may bear rotten fruits: Diversity browsing VP-Trees.- Continuous Similarity Search for Evolving Database.- Taking advantage of highly-correlated attributes in similarity queries with missing values.- Similarity Between Points in Metric Measure Spaces.- High-dimensional Data and Intrinsic Dimensionality.- GTT: Guiding the Tensor Train Decomposition.- Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Data.- ABID: Angle Based Intrinsic Dimensionality.- Sampled Angles in High-Dimensional Spaces.- Local Intrinsic Dimensionality III: Density and Similarity.- Analysing Indexability of Intrinsically High-dimensional Data using TriGen.- Reverse k-Nearest Neighbors Centrality Measures and Local Intrinsic Dimension.- Clustering.- BETULA: Numerically Stable CF-Trees for BIRCH Clustering.- Using a Set of Triangle Inequalities to Accelerate K-means Clustering.- Angle-Based Clustering.- Artificial Intelligence and Similarity.- Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.- SIR: Similar Image Retrieval for Product Search in E-Commerce.- Cross-Resolution deep features based Image Search.- Learning Distance Estimators from Pivoted Embeddings of Metric Objects.- Demo and Position Papers.- Visualizer of Dataset Similarity using Knowledge Graph.- vitrivr-explore: Guided Multimedia Collection Exploration for Ad-hoc Video Search.- Running experiments with confidence and sanity.- Doctoral Symposium.- Temporal Similarity of Trajectories in Graphs.- Relational Visual-Textual Information Retrieval.

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Book SynopsisThis open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation. Table of ContentsPart I: Ecosystem Elements of Big Data Value.- The European Big Data Value Ecosystem.- Stakeholder Analysis of Data Ecosystems.- A Roadmap to Drive Adoption of Data Ecosystems.- Achievements and Impact of the Big Data Value Public-Private Partnership: The Story so Far.- Part II: Research and Innovation Elements of Big Data Value.- Technical Research Priorities for Big Data.- A Reference Model for Big Data Technologies.- Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving Technologies.- A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence.- Data Innovation Spaces.- Part III: Business, Policy, and Societal Elements of Big Data Value.- Big Data Value Creation by Example.- Business Models and Ecosystem for Big Data.- Innovation in Times of Big Data and AI: Introducing the Data-Driven Innovation (DDI) Framework.- The Road to Big Data Standardisation.- The Role of Data Regulation in Shaping AI: An Overview of Challenges and Recommendations for SMEs.- Part IV: Emerging Elements of Big Data Value.- Data Economy 2.0: From Big Data Value to AI Value and a European Data Space.

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Book SynopsisThis book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.*The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives.*The summer school was held virtually.Table of ContentsTutorial Paper.- Don’t Tell Them now (or at all) – End User Notification Duties under GDPR and NIS Directive.- Selected Student Papers.- Ethical Principles for Designing Responsible Offensive Cyber Security Training.- Longitudinal collection and analysis of mobile phone data with local differential privacy.- Privacy-preserving IDS for In-Car-Networks with Local Differential Privacy.- Strong customer authentication in online payments under GDPR and PSD2: a case of cumulative application.- Privacy in Payment in the Age of Central Bank Digital Currency.- Analysing drivers’ preferences for privacy enhancing car-to-car communication systems.- Learning Analytics and Privacy - Respecting Privacy in Digital Learning Scenarios.- Preserving Privacy in Caller ID Applications.- “Identity management by design” with a technical Mediator under the GDPR.- Open about the open-rate? State of email tracking in marketing emails and its effects on user's privacy.- Privacy Respecting Data Sharing and Communication in mHealth: A Case Study.- Privacy-preserving Analytics for Data Markets using MPC.- Towards models for privacy preservation in the face of metadata exploitation.

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Book SynopsisThis textbook covers all central activities of data warehousing and analytics, including transformation, preparation, aggregation, integration, and analysis. It discusses the full spectrum of the journey of data from operational/transactional databases, to data warehouses and data analytics; as well as the role that data warehousing plays in the data processing lifecycle. It also explains in detail how data warehouses may be used by data engines, such as BI tools and analytics algorithms to produce reports, dashboards, patterns, and other useful information and knowledge.The book is divided into six parts, ranging from the basics of data warehouse design (Part I - Star Schema, Part II - Snowflake and Bridge Tables, Part III - Advanced Dimensions, and Part IV - Multi-Fact and Multi-Input), to more advanced data warehousing concepts (Part V - Data Warehousing and Evolution) and data analytics (Part VI - OLAP, BI, and Analytics).This textbook approaches data warehousing from the case study angle. Each chapter presents one or more case studies to thoroughly explain the concepts and has different levels of difficulty, hence learning is incremental. In addition, every chapter has also a section on further readings which give pointers and references to research papers related to the chapter. All these features make the book ideally suited for either introductory courses on data warehousing and data analytics, or even for self-studies by professionals. The book is accompanied by a web page that includes all the used datasets and codes as well as slides and solutions to exercises.Table of Contents1. Introduction.- Part I: Star Schema.- 2. Simple Star Schemas.- 3. Creating Facts and Dimensions: More Complex Processes.- Part II: Snowflake and Bridge Tables.- 4. Hierarchies.- 5. Bridge Tables.- 6. Temporal Data Warehousing.- Part III: Advanced Dimension.- 7. Determinant Dimensions.- 8. Junk Dimensions.- 9. Dimension Keys.- 10. One-Attribute Dimensions.- Part IV: Multi-Fact and Multi-Input.- 11. Multi-Fact Star Schemas.- 12. Slicing a Fact.- 13. Multi-Input Operational Databases.- Part V: Data Warehousing Granularity and Evolution.- 14. Data Warehousing Granularity and Levels of Aggregation.- 15. Designing Lowest-Level Star Schemas.- 16. Levels of Aggregation: Adding and Removing Dimensions.- 17. Levels of Aggregation and Bridge Tables.- 18. Active Data Warehousing.- Part VI: OLAP, Business Intelligence, and Data Analytics.- 19. Online Analytical Processing (OLAP).- 20. Pre- and Post-Data Warehousing.- 21. Data Analytics for Data Warehousing.

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Book SynopsisText Mining with MATLAB® provides a comprehensive introduction to text mining using MATLAB. It is designed to help text mining practitioners, as well as those with little-to-no experience with text mining in general, familiarize themselves with MATLAB and its complex applications. The book is structured in three main parts: The first part, Fundamentals, introduces basic procedures and methods for manipulating and operating with text within the MATLAB programming environment. The second part of the book, Mathematical Models, is devoted to motivating, introducing, and explaining the two main paradigms of mathematical models most commonly used for representing text data: the statistical and the geometrical approach. Eventually, the third part of the book, Techniques and Applications, addresses general problems in text mining and natural language processing applications such as document categorization, document search, content analysis, summarization, question answering, and conversational systems. This second edition includes updates in line with the recently released “Text Analytics Toolbox” within the MATLAB product and introduces three new chapters and six new sections in existing ones. All descriptions presented are supported with practical examples that are fully reproducible. Further reading, as well as additional exercises and projects, are proposed at the end of each chapter for those readers interested in conducting further experimentation. Table of Contents1. Introduction.- PART I: FUNDAMENTALS.- 2. Handling Text Data.- 3. Regular Expressions.- 4. Basic Operations with Strings.- 5. Reading and Writing Files.- 6. The Structure of Language.- PART II: MATHEMATICAL MODELS.- 7. Basic Corpus Statistics.- 8. Statistical Models.- 9. Geometrical Models.- 10. Dimensionality Reduction.- PART III: METHODS AND APPLICATIONS.- 11. Document Categorization.- 12. Document Search.- 13. Content Analysis.- 14. Keyword Extraction and Summarization.- 15. Question Answering and Dialogue.

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Book SynopsisThis book constitutes the refereed proceedings of the 27th China Conference on Information Retrieval, CCIR 2021, held in Dalian, China, in October 2021.The 15 full papers presented were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections: search and recommendation, NLP for IR, IR in Education, and IR in Biomedicine.Table of ContentsSearch and Recommendation.- NLP for IR.- IR in Education.- IR in Biomedicine.

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Book SynopsisThis revised textbook presents updated material on its core content: an end-to-end IoT architecture that is comprised of devices, network, compute, storage, platform, applications along with management and security components. As with the second edition, it is organized into six main parts: an IoT reference model; fog computing and the drivers; IoT management and applications; smart services in IoT; IoT standards; and case studies. This edition’s features include overhaul of the IoT Protocols (Chapter 5) to include an expanded treatment of low-power wide area networks including narrow band IoT (NB-IoT) protocol, updated IoT platforms and capabilities (Chapter 7) to include comparison of commercially available platforms (e.g. AWS IoT Platform, Google Cloud IoT Platform, Microsoft Azure IoT Platform, and PTC ThinkWorx), updated security (Chapter 8) to include approaches for securing IoT devices with examples of IoT devices used in security attacks and associated solutions including MUD and DICE, and finally new Appendix B to include six IoT project detailed for students.Table of ContentsIntroduction.- Part I: IoT Overview and Architecture.- IoT Timeline.- IoT Reference Model.- Evolution of IoT Protocol Stack.- State of the Industry.- Part II: Fog Computing.- Why Fog.- Defining the Fog.- Data In Motion.- Part III: IoT Management and Applications.- IoT Management.- IoT Security.- IoT Traffic Engineering.- IoT Applications.- Part IV: IoT-Based Smart Services.- Smart Service Framework.- Creating Smart Services.- Service Creation, development and delivery.- Ecosystems Partners.- Services reference architecture.- Part V: IoT Standards.- OneM2M.- ATSI.- ETSI.- IEEE.- Part VI: Invited Chapters.- IoT Business Models.- Open Source Initiatives.- Data in Motion. The Blockchain in IoT.- Conclusion.

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Book SynopsisThis revised textbook presents updated material on its core content: an end-to-end IoT architecture that is comprised of devices, network, compute, storage, platform, applications along with management and security components. As with the second edition, it is organized into six main parts: an IoT reference model; fog computing and the drivers; IoT management and applications; smart services in IoT; IoT standards; and case studies. This edition’s features include overhaul of the IoT Protocols (Chapter 5) to include an expanded treatment of low-power wide area networks including narrow band IoT (NB-IoT) protocol, updated IoT platforms and capabilities (Chapter 7) to include comparison of commercially available platforms (e.g. AWS IoT Platform, Google Cloud IoT Platform, Microsoft Azure IoT Platform, and PTC ThinkWorx), updated security (Chapter 8) to include approaches for securing IoT devices with examples of IoT devices used in security attacks and associated solutions including MUD and DICE, and finally new Appendix B to include six IoT project detailed for students.Table of ContentsIntroduction.- Part I: IoT Overview and Architecture.- IoT Timeline.- IoT Reference Model.- Evolution of IoT Protocol Stack.- State of the Industry.- Part II: Fog Computing.- Why Fog.- Defining the Fog.- Data In Motion.- Part III: IoT Management and Applications.- IoT Management.- IoT Security.- IoT Traffic Engineering.- IoT Applications.- Part IV: IoT-Based Smart Services.- Smart Service Framework.- Creating Smart Services.- Service Creation, development and delivery.- Ecosystems Partners.- Services reference architecture.- Part V: IoT Standards.- OneM2M.- ATSI.- ETSI.- IEEE.- Part VI: Invited Chapters.- IoT Business Models.- Open Source Initiatives.- Data in Motion. The Blockchain in IoT.- Conclusion.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the 7th EAI International Conference on Smart Objects and Technologies for social Good, GOODTECHS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were selected from 53 submissions and issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.Table of ContentsLearning.- Balancing activity recognition and privacy preservation with a multi-objective evolutionary algorithm.- Biometric data capture as a way to identify lack f physical activity in daily life.- Comparative Analysis of Process Mining Algorithms in Python.- COVID-19 Next Day Trend ForecastAnomaly Detection in Cellular IoT with Machine Learning.- Internet of Things.- A Smart IoT System for Water Monitoring and Analysis.- Decentralising the Internet of Medical Things with Distributed Ledger Technologies and Off-Chain Storages: a Proof of Concept.- Towards a Monitoring Framework for Users of Retirement Houses with Mobile Sensing.- Temporal authorization graphs: Pros, Cons and Limits.- Advanced 5G Network Slicing Isolation Using Enhanced VPN+ for Healthcare Verticals.- Social considerations of technology.- GuideSwarm: A Drone Network Design to Assist Visually-impaired People.- LISA - Lingua Italiana dei Segni Accessibile: A Progressive Web App to Support Communication Between Deaf People and Public Administrations.- Building emotionally stable, inclusive, and healthy communities with ICT: from state of the art to PSsmile app.- issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.- Machine Management Technology for Institutional Environment in Pandemic Times.- Technology and ageing.- Augmented Reality, Vrtual Reality and Mixed Reality as driver tools for promoting cognitive activity and avoid isolation in ageing population.- Ageing@home: A secure 5G welfare technology solution for elderlies.- Defining the instruments for zero-measurement of psychological well-being at older adults.- DERCA Tool: A set of Tests for Analysis of Elderly Dexterity in Information and Communications Technologies.- Building Inclusive Environments for All Ages with Citizens.- Healthcare.- The New Era of Technology applied to Cardiovascular Patients: State-of-the-art and Questionnaire applied for a System Proposal.- Co-design and engineering of user requirements for a novel ICT healthcare solution in Murcia, Spain.- What do nurses and carers in Portual wish and need from a digital intelligent assistant for nursing applications.- Examining Furniture Preferences of The Elderly in Greece.

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