Expert systems / knowledge-based systems Books

Book SynopsisFeedback control systems is an important course in aerospace engineering, chemical engineering, electrical engineering, mechanical engineering, and mechatronics engineering, to name just a few. Feedback control systems improve the system's behavior so the desired response can be acheived. The first course on control engineering deals with Continuous Time (CT) Linear Time Invariant (LTI) systems. Plenty of good textbooks on the subject are available on the market, so there is no need to add one more. This book does not focus on the control engineering theories as it is assumed that the reader is familiar with them, i.e., took/takes a course on control engineering, and now wants to learn the applications of MATLAB® in control engineering. The focus of this book is control engineering applications of MATLAB® for a first course on control engineering.Table of ContentsPreface.- Acknowledgments.- Introduction to MATLAB®.- Commonly Used Commands in Analysis of Control Systems.- Introduction to Simulink®.- Controller Design in MATLAB®.- Introduction to System Identification Toolbox™.- References.- Authors' Biographies.

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Book SynopsisA lot of digital ink has been spilled on "big data" over the past few years. Most of this surge owes its origin to the various types of unstructured data in the wild, among which the proliferation of text-heavy data is particularly overwhelming, attributed to the daily use of web documents, business reviews, news, social posts, etc., by so many people worldwide.A core challenge presents itself: How can one efficiently and effectively turn massive, unstructured text into structured representation so as to further lay the foundation for many other downstream text mining applications? In this book, we investigated one promising paradigm for representing unstructured text, that is, through automatically identifying high-quality phrases from innumerable documents. In contrast to a list of frequent n-grams without proper filtering, users are often more interested in results based on variable-length phrases with certain semantics such as scientific concepts, organizations, slogans, and so on. We propose new principles and powerful methodologies to achieve this goal, from the scenario where a user can provide meaningful guidance to a fully automated setting through distant learning. This book also introduces applications enabled by the mined phrases and points out some promising research directions.Table of ContentsAcknowledgments.- Introduction.- Quality Phrase Mining with User Guidance.- Automated Quality Phrase Mining.- Phrase Mining Applications.- Bibliography.- Authors' Biographies .

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Book SynopsisSocial network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.Table of ContentsA Randomized Approach for Structural and Message based Private Friend Recommendation in Online Social Networks; B. K. Samanthula, W.Jiang.- Context Based Semantic Relations in Tweets; O. Ozdikis et al.- Fast exact and approximate computation of betweenness centrality in social networks; M. Baglioni et al.- Network Simulation; E. Franchi.- Early Stage Conversation Catalysts on Entertainment-Based Web Forums; J. Lanagan et al.- Predicting Users Behaviours in Distributed Social Networks Using Community Analysis ; B. Ngonmang et al.- What should we protect? Defining differential privacy for social network analysis; C. Task, C.Clifton.- Complex Network Analysis of Research Funding: A Case Study of NSF Grants; H. Kardes et al.- Community Evolutionary Events in Online Social Networks; M. Abulaish, S. Yousuf Bhat.-@Rank: Personalized Centrality Measure for Email Communication Networks; P. Lubarski, M. Morzy.-Twitter Sentiment Analysis: How To Hedge Your Bets In The Stock Markets; T.Rao, S. Srivastava.- The Impact of Measurement Time on Subgroup Detection in Online Communities; S. Zeini et al.- Spatial and Temporal Evaluation of Network-Based Analysis of Human Mobility; M. Coscia et al.- An Ant based Particle Swarm Optimization Algorithm for Maximum Clique Problem in Social networks; M. Soleimani-pouri et al.- XEngine: An XML Search Engine for Social Groups; K.Taha.- Size, diversity and components in the network around an entrepreneur: Shaped by culture and shaping embeddedness of firm relations; M. Cheraghi, T.Schott .- Content Mining of Microblogs; M.Ö. Cingiz, B. Diri.

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Book SynopsisThe book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.Table of ContentsPredicting human behavior based on web search activity: Greek referendum of 2015.- Compact Video Description and Representation for Automated Summarization of Human Activities.- Attribute Learning for Network Intrusion Detection.- A Fast Deep Convolutional Neural Network for face detection in Big Visual Data.- Learning Symbols by Neural Network.- Designing HMMs models in the age of Big Data.- Extended Formulations for Online Action Selection on Big Action Sets.- Multi-Task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports.- An infrastructure and approach for infering knowledge over Big Data in the Vehicle Insurance Industry.- Unified Retrieval Model of Big Data.- Adaptive Elitist Differential Evolution Extreme Learning Machines on Big Data: Intelligent Recognition of Invasive Species.

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Book SynopsisThis book constitutes the thoroughly refereed post-conference proceedings of the Third International ICST Conference on Sensor Systems and Software, S-Cube 2012, held in Lisbon, Portugal in June 2012. The 12 revised full papers presented were carefully reviewed and selected from over 18 submissions and four invited talks and cover a wide range of topics including middleware, frameworks, learning from sensor data streams, stock management, e-health, and Web Of Things.Table of ContentsFast conference proceedings.-State-of-the-art report.-Up to date results

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Book SynopsisFür die Printmedienunternehmen haben sich durch das Internet neue Geschäftsfelder eröffnet: Informationen werden sowohl für die Papier- als auch für die Onlineausgabe aufbereitet. Neue Möglichkeiten in der Zusammenarbeit mit Kunden und Produktionspartnern entstehen. Der Leser erhält einen umfassenden Überblick über die neuen Produkte und Prozesse und wird systematisch durch die Begriffsvielfalt geführt; zahlreiche Beispiele veranschaulichen die Anwendungen wie Online-Editiersysteme, webbasierte Projektmanagementtools oder Online-Tracking von Druckaufträgen. Das Thema wird aus zwei Blickwinkeln betrachtet: dem des Unternehmens, das E-Business zur Verbesserung der eigenen Prozesse nutzt, und dem des Printmediendienstleisters, der E-Business-Services für seine Kunden bereitstellt und im Produktionsprozess nutzt. Das Buch liefert Entscheidungshilfen, welche Anwendungen für betriebliche Fragestellungen den größtmöglichen Nutzen versprechen. Ein unentbehrliches Nachschlagewerk für Entscheidungsträger.Table of Contents1 Neue Produkte und Dienstleistungen.- 1.1 Kernkompetenz Druck oder crossmedialer Dienstleister — eine strategische Entscheidung.- 1.2 Internetprasenzen erstellen und pflegen.- 1.3 Datenbanken aufbauen, erweitern und Verfugbarkeit sicherstellen durch Media-Asset-Managernent-Systeme.- 1.4 Database Publishing — aus Datenbanken heraus produzieren.- 1.5 Content-Management-Systeme auswahlen, einrichten und selbst nutzen.- 1.6 E-Commerce-Systeme integrieren.- 1.7 E-Learning-Anwendungen entwickeln.- 1.8 Qualitatssicherung als Dienstleistung.- 2 Prozesseffizienz durch kundenintegrierte Produktion.- 2.1 Standarddatenformate als Voraussetzung fur die vernetzte Produktion.- 2.1.1 PDF/X-3 — der Standard im technischen Workflow.- 2.1.2 JDF — auf dem Weg zum Standard in der vernetzten Produktion.- 2.1.3 XML — der Standard im E-Business.- 2.2 Prozesseffizienz durch Selbstbedienung: der self-directed-customer.- 2.2.1 Online-Kalkulation — schneller als der Kunde schafft es kein Vertrieb.- 2.2.2 Online-Auftragserteilung.- 2.2.3 Online-Preflight.- 2.2.4 Daten andern und Softproof freigeben — das Prinzip des Web-Printing.- 2.2.5 Order-Tracking — Auftragsverfolgung durch den Kunden.- 2.2.6 Angebots- und Auftragsarchivierung.- 2.2.7 Lagerabrufsysteme.- 2.2.8 Online-Bestellsysteme.- 2.2.8.1 Spezialanwendungen fiir Copyshops Beispiel Copymobil.de.- 2.2.8.2 Spezialanwendung fur Mailings Beispiel Mailingfactory der Deutschen Post.- 2.2.8.3 Kundenindividuelles Online-Bestellsystem am Beispiel PSH iWayPrime — Integration bis zur Druckmaschine.- 2.2.8.4 Kundenindividuelles Online-Bestellsystem am Beispiel PrintVis — Integration in die betriebswirtschaftlichen Systeme.- 2.2.8.5 Corporate-Design-Portal am Beispiel der Adam Opel AG.- 2.2.9 Vorgehensweise bei der Einfiihrung von self-directed-customer-Systemen.- 2.3 Prozesseffizienz in der Zusammenarbeit — der Kunde als Co-Produzent.- 2.3.1 Änderungen und Freigaben.- 2.3.1.1 Änderungen und Freigaben im PDF-Dokument.- 2.3.1.2 Änderungen und Freigaben im Team — Beispiel Synapse Insite.- 2.3.2 Online-Editiersysteme — Beispiel StreamGuide Web.- 2.3.3 Remote Proofing.- 3 E-Business fuür Einkäufer.- 3.1 Beschaffungsprozesse beim Kunden und Potenziale des E-Procurement.- 3.2 Online-Marktpäitze — der Verkauf öber Drucksachenvermittler.- 3.3 Angebots- und Auftragsverwaltungssysteme — Effizienz im Einkauf.- 3.3.1 Lieferantenauswahl.- 3.3.2 Auftragsabwicklung.- 4 E-Business fur Druckereien.- 4.1 Marketing und Vertrieb.- 4.1.1 Die eigene Internetprasenz — Neukundengewinnung und Kundenbindung.- 4.1.1.1 Inhalte der Internetprasenz.- 4.1.1.2 E-Marketing.- 4.1.2 Ausschreibungenauf Kunden zugehen ohne Kundenkontakt.- 4.1.3 Reverse Auction — Drucken urn jeden Preis?.- 4.2 Beschaffung.- 4.2.1 Papiereinkauf.- 4.2.1.1 SchneiderSoehne-online.com — kundenindividuelle Preise, Verfiigbarkeit und Liefertermin auf einen Klick.- 4.2.1.2 Marktplatz fur die Papierbeschaffung — Beispiel eN Papiervertriebs GmbH.- 4.2.2 Druckfarben — Beispiel BASF Drucksysteme.- 4.2.3 Bild, Schrift, Grafik & mehr.- 4.2.4 Produktionspartner — wie man neue Zulieferer und freiberufiiche Mitarbeiter findet.- 5 Nachwort.- 6 Glossar.

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Book SynopsisPart I: Data Lakehouses, Iceberg, Batch ETL, and Orchestration.- Chapter 1: Foundational Data Engineering Concepts.- Chapter 2: Building a Data Lakehouse with Apache Iceberg.- Chapter 3: Batch ETL Pipeline with Apache Spark.- Chapter 4: Data Visualization with Apache Superset.- Chapter 5: Workflow Orchestration with Apache Airflow.- Part II: Streaming Data and Real-time Analytics. - Chapter 6: Change Data Capture with Debezium and Kafka.- Chapter 7: Low-latency Analytics Dashboard with ClickHouse.- Chapter 8: Real-time Fraud Detection with Apache Flink.- Part III: Machine Learning and Generative AI.- Chapter 9: Building a Product Recommendation Engine with Spark MLlib.- Chapter 10: Vector Similarity Search with Postgres and pgvector.

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Book SynopsisThe book is the complete introduction and applications guide to this new technology. This book introduces the reader to features and gives an overview of geometric modeling techniques, discusses the conceptual development of features as modeling entities, illustrates the use of features for a variety of engineering design applications, and develops a set of broad functional requirements and addresses high level design issues.Table of ContentsBACKGROUND. Geometric Modeling. FUNDAMENTALS. Feature Concepts. Feature Creation Techniques. APPLICATION OF FEATURES. Features in Design. Features in Manufacturing. Feature Mapping and Data Exchange. DESIGN AND IMPLEMENTATION. Design-by-Features Techniques. Feature Recognition Techniques. Implementation Tools. Feature-Based Process Planning. BEYOND FEATURES. Future CAD/CAM Technologies. Appendices. Index.

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Book SynopsisThis book covers the development of intelligent systems using a mixture of scientific, philosophical, and engineering concepts. It provides an expert blend of theory and practice in intelligent systems design and uses real-world examples to illustrate technical concepts.Table of ContentsPreface. Emergence of a Theory. Knowledge. Perception. Goal Seeking and Planning. A Reference Model Architecture. Behavior Generation. World Modeling, Value Judgment, and Knowledge Representation. Sensory Processing. Engineering Unmanned Ground Vehicles. Future Possibilities. References. Index.

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Book SynopsisProvides an integrated view of the five kinds of enabling technologies in terms of knowledge media architectures such as: multimedia and hypermedia, object oriented GUI and visual programming, reusable component software and component integration, network publishing and electronic commerce, and object oriented and multimedia databases.Trade Review"…very interesting…recommended…" (E-Streams, Vol. 7, No. 4)Table of ContentsPreface. 1 Overview and Introduction. 1.1 Why Meme Media? 1.2 How Do Meme Media Change the Reuse of Web Contents? 1.3 How Do Meme Media Work? 1.4 Frequently Asked Questions and Limitations. 1.5 Organization of this Book. 2 Knowledge Media and Meme Media. 2.1 Introduction to Knowledge Media and Meme Media. 2.2 From Information Technologies to Media Technologies. 2.3 Summary. References. 3 Augmentation Media Architectures and Technologies—A Brief Survey. 3.1 History and Evolution of Augmentation Media. 3.2 History and Evolution of Knowledge-Media Architectures. 3.3 Meme Media and their Applications. 3.4 Web Technologies and Meme Media. 3.5 Summary. References. 4 An Outline of IntelligentPad and Its Development History. 4.1 Brief Introduction to IntelligentPad. 4.2 IntelligentPad Architecture. 4.3 Worldwide Marketplace Architectures for Pads. 4.4 End-User Computing and Media Toolkit System. 4.5 Open Cross-Platform Reusability. 4.6 Reediting and Redistribution by End-Users. 4.7 Extension toward 3D Representation Media. 4.8 Summary. References. 5 Object Orientation and MVC. 5.1 Object-Oriented System Architecture—A Technical Introduction. 5.2 Class Refinement and Prototyping. 5.3 Model, View, Controller. 5.4 Window Systems and Event Dispatching. 5.5 Summary. References. 6 Component Integration. 6.1 Object Reusability. 6.2 Components and Application Linkage. 6.3 Compound Documents and Object Embedding/Linking. 6.4 Generic Components. 6.5 What to Reuse—Components or Sample Compositions? 6.6 Reuses and Maintenance. 6.7 Integration of Legacy Software. 6.8 Distributed Component Integration and Web Technologies. 6.9 Summary. References. 7 Meme Media Architecture. 7.1 Current Megatrends in Computer Systems. 7.2 Primitive Media Objects. 7.3 Composition through Slot Connections. 7.4 Compound-Document Architecture. 7.5 Standard Messages between Pads. 7.6 Physical and Logical Events and their Dispatching. 7.7 Save and Exchange Format. 7.8 Copy and Shared Copy. 7.9 Global Variable Pads. 7.10 Summary. References. 8 Utilities for Meme Media. 8.1 Generic Utility Functions as Pads. 8.2 FieldPad for the Event Sharing. 8.3 StagePad for Programming User Operations. 8.4 Geometrical Management of Pads. 8.5 Proxy Pads to Assimilate External Objects. 8.6 Legacy Software Migration. 8.7 Special Effect Techniques. 8.8 Expression Pad. 8.9 Transformation Pads. 8.10 Summary. References. 9 Multimedia Application Framework. 9.1 Component Pads for Multimedia Application Frameworks. 9.2 Articulation of Objects. 9.3 Hypermedia Framework. 9.4 Summary. References. 10 IntelligentPad and Databases. 10.1 Relational Databases, Object-Oriented Databases, and Instance Bases. 10.2 Form Bases. 10.3 Pads as Attribute Values. 10.4 Multimedia Database. 10.5 Hypermedia Database. 10.6 Geographical Information Databases. 10.7 Content-Based Search and Context-Based Search. 10.8 Management and Retrieval of Pads. 10.9 Summary. References. 11 Meme Pool Architectures. 11.1 Pad Publication Repository and the WWW. 11.2 Pad Publication and Pad Migration. 11.3 Web Pages as Pad Catalog. 11.4 URL-Anchor Pads. 11.5 HTMLViewerPad with Embedded Arbitrary Composite Pads. 11.6 New Publication Media. 11.7 Annotation on Web Pages. 11.8 Piazza as a Meme Pool. 11.9 Reediting and Redistributing Web Content as Meme Media Objects. 11.10 Redistribution and Publication of Meme Media Objects as Web Content. 11.11 Summary. References. 12 Electronic Commerce for Pads. 12.1 Electronic Commerce. 12.2 From Pay-per-Copy to Pay-per-Use. 12.3 Digital Accounting, Billing, and Payment. 12.4 Ecology of Pads in the Market. 12.5 Superdistribution of Pads. 12.6 Pad Integration and Package Business. 12.7 Summary. References. 13 Spatiotemporal Editing of Pads. 13.1 Geometrical Arrangement of Pads. 13.2 Time-Based Arrangement of Pads. 13.3 Spatiotemporal Editing of Pads. 13.4 Information Visualization. 13.5 Summary. References. 14 Dynamic Interoperability of Pads and Workflow Modeling. 14.1 Dynamic Interoperability of Pads Distributed across Networks. 14.2 Extended Form-Flow System. 14.3 Pad-Flow Systems. 14.4 Dynamic Interoperability across Networks. 14.5 Workflow and Concurrent Engineering. 14.6 Summary. References. 15 Agent Media. 15.1 Three Different Meanings of Agents. 15.2 Collaborative-and-Reactive Agents and Pads. 15.3 Mobile Agents and Pads. 15.4 Pad Migration and Script Languages. 15.5 Summary. References. 16 Software Engineering with IntelligentPad. 16.1 IntelligentPad as Middleware. 16.2 Concurrent Engineering in Software Development. 16.3 Components and Their Integration. 16.4 Patterns and Frameworks in IntelligentPad. 16.5 From Specifications to a Composite Pad. 16.6 Pattern Specifications and the Reuse of Pads. 16.7 IntelligentPad as a Software Development Framework. 16.8 Summary. References. 17 Other Applications of IntelligentPad. 17.1 Capabilities Brought by the Implementation in IntelligentPad. 17.2 Tool Integration Environments and Personal Information Management. 17.3 Educational Applications. 17.4 Web Page Authoring. 17.5 Other Applications. 17.6 Summary. 18 3D Meme Media. 18.1 3D Meme Media IntelligentBox. 18.2 3D Application Systems. 18.3 IntelligentBox Architecture. 18.4 Example Boxes and Utility Boxes. 18.5 Animation with IntelligentBox. 18.6 Information Visualization with IntelligentBox. 18.7 Component-Based Framework for Database Reification. 18.8 Virtual Scientific Laboratory Framework. 18.9 3D Meme Media and a Worldwide Repository of Boxes as a Meme Pool. 18.10 Summary. References. 19 Organization and Access of Meme Media Objects. 19.1 Organization and Access of Intellectual Resources. 19.2 Topica Framework. 19.3 The Application Horizon of the Topica Framework. 19.4 Queries over the Web of Topica Documents. 19.5 Related Research. 19.6 Summary. References. 20 IntelligentPad Consortium and Available Software. 20.1 IntelligentPad Consortium. 20.2 Available Software. 20.3 Concluding Remarks. Author Index. Subject Index. About the Author.

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Book SynopsisIncluding contributions from leading experts in the field, this book covers applications and developments of heuristic search methods for solving complex optimization problems. The book covers various local search strategies including genetic algorithms, simulated annealing, tabu search and hybrids thereof.Table of ContentsPartial table of contents: Modern Heuristic Techniques. TECHNIQUES. Localized Simulated Annealing in Constraint Satisfaction andOptimization. Observing Logical Interdependencies in Tabu Search: Methods andResults. Reactive Search: Toward Self-Tuning Heuristics. Integrating Local Search into Genetic Algorithms. CASE STUDIES. Local Search for Steiner Trees in Graphs. Local Search Strategies for the Vehicle Fleet Mix Problem. A Tabu Search Algorithm for Some Discrete-Continuous SchedulingProblems. The Analysis of Waste Flow Data from Multi-Unit IndustrialComplexes Using Genetic Algorithms. The Evolution of Solid Object Designs Using GeneticAlgorithms. The Convoy Movement Problem with Initial Delays. A Brief Comparison of Some Evolutionary Optimization Methods. Index.

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Book SynopsisProfessor Judea Pearl won the 2011 Turing Award for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning. This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988-2001), and causality, recent period (2002-2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers that analyze, extend, or assess the influence of Pearl''s work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him.

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Book SynopsisProfessor Judea Pearl won the 2011 Turing Award ""for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning."" This book contains the original articles that led to the award, as well as other seminal works.

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Book SynopsisOffers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. The book provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being.

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Book SynopsisOffers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. The book provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being.

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Book SynopsisDesign for large-scale, high-performance queries using Snowflake's query processing engine to empower data consumers with timely, comprehensive, and secure access to data. This book also helps you protect your most valuable data assets using built-in security features such as end-to-end encryption for data at rest and in transit. It demonstrates key features in Snowflake and shows how to exploit those features to deliver a personalized experience to your customers. It also shows how to ingest the high volumes of both structured and unstructured data that are needed for game-changing business intelligence analysis.Mastering Snowflake Solutionsstarts with a refresher on Snowflake's unique architecture before getting into the advanced concepts that make Snowflake the market-leading product it is today. Progressing through each chapter, you will learn how to leverage storage, query processing, cloning, data sharing, and continuous data protection features. This approach allows for greater Table of Contents1. Snowflake Architecture2. Data Movement3. Cloning4. Managing Security and User Access Control 5. Protecting Data in Snowflake6. Business Continuity and Disaster Recovery7. Data Sharing and the Data Cloud8. Programming9. Advanced Performance Tuning10. Developing Applications in Snowflake

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Book SynopsisThis book is your practical and comprehensive guide to learning Google Cloud Platform (GCP) for data science, using only the free tier services offered by the platform. Data science and machine learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. GCP offers a range of data science services that can be used to store, process, and analyze large datasets, and train and deploy machine learning models. The book is organized into seven chapters covering various topics such as GCP account setup, Google Colaboratory, Big Data and Machine Learning, Data Visualization and Business Intelligence, Data Processing and Transformation, Data Analytics and Storage, and Advanced Topics. Each chapter provides step-by-step instructions and examples illustrating how to use GCP services for data science and big data projects. Readers will learn how to set up a Google Colaboratory account and run Jupyternotebooks, access GCP services and data from Colaboratory, use BigQuery for data analytics, and deploy machine learning models using Vertex AI. The book also covers how to visualize data using Looker Data Studio, run data processing pipelines using Google Cloud Dataflow and Dataprep, and store data using Google Cloud Storage and SQL. What You Will LearnSet up a GCP account and projectExplore BigQuery and its use cases, including machine learningUnderstand Google Cloud AI Platform and its capabilities Use Vertex AI for training and deploying machine learning modelsExplore Google Cloud Dataproc and its use cases for big data processingCreate and share data visualizations and reports with Looker Data StudioExplore Google Cloud Dataflow and its use cases for batch and stream data processing Run data processing pipelines on Cloud DataflowExplore Google Cloud Storageand its use cases for data storage Get an introduction to Google Cloud SQL and its use cases for relational databases Get an introduction to Google Cloud Pub/Sub and its use cases for real-time data streamingWho This Book Is ForData scientists, machine learning engineers, and analysts who want to learn how to use Google Cloud Platform (GCP) for their data science and big data projectsTable of ContentsChapter 1: Introduction to GCP.- Chapter 2: Google Colaboratory.- Chapter 3: Big Data and Machine Learning.- Chapter 4: Data Visualization and Business Intelligence.- Chapter 5: Data Processing and Transformation.- Chapter 6: Data Analytics and Storage.- Chapter 7: Advanced Topics.

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Book SynopsisThe disciplines of accounting and finance have been rapidly changing in recent years. The methods and techniques now being used have created a new language for managers, students, practitioners, academics and all those who are connected in some way with business and investment activities. To understand and work within an environment that is in a constant state of flux can be challenging and this book provides a resource of information and guidance.The Guide focuses specifically on the terms used in accounting and finance. Important terms and phrases are identified but with a much longer, in-depth explanation than you would normally find in a dictionary. Not only does each entry gives a thorough explanation of each term, most entries provide two or more references to academic articles that go into much greater depth. Hence, the entries give the reader immediate access to the literature.The Guide also comments on the contribution of the articles which adds to our knowledge. This approach allows the reader to obtain a much deeper level of understanding much more quickly than is available from the usual dictionary. At the end of the book, the full reference to all the articles that have been cited in the text is given including a list of the many acronyms used in the world of accounting and finance.

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Book SynopsisEnterprise Systems have been used for many years to integrate technology with the management of an organization but rapid technological disruptions are now creating new challenges and opportunities that require urgent consideration. This book reappraises the implementation and management of Enterprise Systems in the digital age and investigates the vital link between business processes, information technology and the Internet for an organization’s competitive advantage and success.This book primarily focuses on the implementation, operation, management and integration of Enterprise Systems with fastemerging disruptive technologies such as blockchains, big data, cryptocurrencies, artificial intelligence, cloud computing, data mining and data analytics. These disruptive technologies are now becoming mainstream and the book proposes several innovations that organizations need to adopt to remain competitive within this rapidly changing landscape. In addition, it examines Enterprise Systems, their components, architecture, and applications and enlightens readers on the benefits and shortcomings of implementing them. This book contains primary research on organizations, case studies, and benchmarks ERP implementation against international best practice.

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Book SynopsisEnterprise Systems have been used for many years to integrate technology with the management of an organization but rapid technological disruptions are now creating new challenges and opportunities that require urgent consideration. This book reappraises the implementation and management of Enterprise Systems in the digital age and investigates the vital link between business processes, information technology and the Internet for an organization’s competitive advantage and success.This book primarily focuses on the implementation, operation, management and integration of Enterprise Systems with fastemerging disruptive technologies such as blockchains, big data, cryptocurrencies, artificial intelligence, cloud computing, data mining and data analytics. These disruptive technologies are now becoming mainstream and the book proposes several innovations that organizations need to adopt to remain competitive within this rapidly changing landscape. In addition, it examines Enterprise Systems, their components, architecture, and applications and enlightens readers on the benefits and shortcomings of implementing them. This book contains primary research on organizations, case studies, and benchmarks ERP implementation against international best practice.

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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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