Expert systems / knowledge-based systems Books

Book SynopsisLearn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You''ll Learn Become fluent in the essential concepts and terminology of data science and data engineering  Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling ofTable of Contents

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Book SynopsisLeverage Apache Spark within a modern data engineering ecosystem.This hands-on guide will teach you how to write fully functional applications, follow industry best practices, and learn the rationale behind these decisions. With Apache Spark as the foundation, you will follow a step-by-step journey beginning with the basics of data ingestion, processing, and transformation, and ending up with an entire local data platform running Apache Spark, Apache Zeppelin, Apache Kafka, Redis, MySQL, Minio (S3), and Apache Airflow. Apache Spark applications solve a wide range of data problems from traditional data loading and processing to rich SQL-based analysis as well as complex machine learning workloads and even near real-time processing of streaming data. Spark fits well as a central foundation for any data engineering workload. This book will teach you to write interactive Spark applications using Apache Zeppelin notebooks, write and compilereusable applications and modules, and fully testTable of Contents​Part I. The Fundamentals of Data Engineering with Spark1. Introduction to Modern Data Engineering2. Getting Started with Apache Spark3. Working with Data4. Transforming Data with Spark SQL and the DataFrame API5. Bridging Spark SQL with JDBC6. Data Discovery and the Spark SQL Catalog7. Data Pipelines & Structured Spark ApplicationsPart II. The Streaming Pipeline Ecosystem8. Workflow Orchestration with Apache Airflow9. A Gentle Introduction to Stream Processing10. Patterns for Writing Structured Streaming Applications11. Apache Kafka & Spark Structured Streaming12. Analytical Processing & InsightsPart III. Advanced Techniques13. Advanced Analytics with Spark Stateful Structured Streaming14. Deploying Mission Critical Spark Applications on Spark Standalone15. Deploying Mission Critical Spark Applications on Kubernetes

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Book SynopsisMaster the tricks and techniques of business analytics consulting, specifically applicable to small-to-medium businesses (SMEs). Written to help you hone your business analytics skills, this book applies data science techniques to help solve problems and improve upon many aspects of a business'' operations. SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing with the ongoing digital revolution. The topics covered in the books will help to provide the knowledge leverage needed for implementing data science in small business. The demand of small business for data analytics are in conjunction with the growing number of freelance data science consulting opportunities; hence this book will provide insight on how to navigate this new terrain. This book uses a do-it-yourself approach to analytics and introduces tools that are easily available online and are non-programming based. Data scienceTrade Review“By reading the book and working out the use case, subject matter experts will be able to get a coherent roadmap to the main techniques available for both descriptive and predictive data analytics, as well as be able to provide simple services related to their company data and future prospects.” (Rosario Uceda-Sosa, Computing Reviews, October 2, 2023)Table of Contents​ INTRODUCTIONWe introduce data science generally and narrow it down to data science for business which is also referred to as business analytics. We then give a detailed explanation of the process involved in business analytics in form of the business analytics journey. In this journey, we explain what it takes from start to finish to carry out an analytics project in the business world, focusing on small business consulting, even though the process is generic to all types of business, small or large. We also give a description of what small business refers to in this book and the peculiarities of navigating an analytics project in such a terrain. To conclude the chapter, we talk about the types of analytics problems that is common to small business and the tools available to solve these problems given the budget situation of small businesses when it comes to analytics project.· DATA SCIENCE· DATA SCIENCE FOR BUSINESS· BUSINESS ANALYTICS JOURNEY· SMALL AND MEDIUM BUSINESS (SME)· BUSINESS ANALYTICS IN SMALL BUSINESS· TYPES OF ANALYTICS PROBLEMS IN SME· ANALYTICS TOOLS FOR SMES· ROAD MAPS TO THIS BOOK· PROBLEMS· REFERENCES CHAPTER 1: DATA FOR ANALYSIS IN SMALL BUSINESSIn this chapter, we would look at the various sources of data generally and in small business. This chapter is important because the major challenge of consulting for small business is the lack of data or quality data for analysis. This chapter will therefore detail the sources of data for analysis explaining first the type or form that data exists and some general ideas of how to collect such data. It gives an overview on data quality and integrity issues and touches on data literacy. The chapter also includes the typical data preparation procedures for the common types of techniques used in small business analytics and by extension used in this book. To conclude the chapter, we look at data visualization, particularly towards preparing data for various analytics task as explained in section 1.3.· SOURCE OF DATA· DATA QUALITY & INTEGRITY· DATA GOVERNANCE· DATA PREPARATION· DATA VISUALIZATION· PROBLEMS· REFERENCESCHAPTER 2: BUSINESS ANALYTICS CONSULTINGIn this chapter, we will look at business analytics consulting, particularly what the concept implies and how to build such a career path. We will explain the types of business analytics consulting that exist and then narrow it down to how to navigate the world of business analytics consulting for small business. In this chapter, we will look at how to manage a typical analytics project and measure the success of analytics projects. In conclusion, we will discuss issues revolving around how to bill analytics project particularly as a consultant.· BUSINESS ANALYTICS CONSULTING· MANAGING ANALYTICS PROJECT· SUCCESS METRICS IN ANALYTICS PROJECT· BILLING ANALYTICS PROJECT· PROBLEMS· REFERENCESCHAPTER 3: BUSINESS ANALYTICS CONSULTING PHASESIn this chapter we will look at the stages involved business analytics consulting, particularly when the analytics service is offered as a product from either within or outside the business. We will look at the proposal and initial analysis stage which gives direction to the analytics project. Then we look at the details involved in the pre-engagement, engagement and post engagement phase. It is important to know that the stages are presented in a typical or generic way but when implemented, there might be reason to modify or customize them for the application scenario.· PROPOSAL & INITIAL ANALYSIS· PRE- ENGAGEMENT PHASE· ENGAGEMENT PHASE· POST ENGAGEMENT PHASE· PROBLEMS· REFERENCES CHAPTER 4: DESCRIPTIVE ANALYTICS TOOLSThis chapter is focused on the mostly common descriptive analytics tools used in business generally and specifically in small businesses. The chapter will help to use descriptive analytics tools to understand your business and make recommendations that can improve your business profits. For small business, descriptive analytics helps SMEs to make sense of available data in order to monitor business indicators at a glance, helps SME owners to observe sales trends and patterns on an overall basis, as well as deep-dive into product categories and customer groups. It also helps SME’s to plan product strategy, pricing policies that will maximize their projected revenues and derive a lot of valuable insights for getting more customers. · INTRODUCTION· BAR CHART· HISTOGRAM· LINE GRAPHS· SCATTER PLOTS· PACKED BUBBLES CHARTS· HEAT MAPS· GEOGRAPHICAL MAPS· A PRACTICAL BUSINESS PROBLEM I· PROBLEMS· REFERENCES CHAPTER 5: PREDICTION TECHNIQUESIn this chapter, we will explore the popular techniques used for prediction, particularly in retails business. The approach used in explaining these techniques us to use them in solving a business problem. The second business problem to be addressed is the sales prediction problem which is common in retail business. The chapter first explain the fundamental concept of prediction techniques, next we look at how such techniques are evaluated. After this, we describe the business problem we intend solving. We then pick each of the selected techniques one by one and explain the algorithms involved and how they can be used to solve the problem described. The prediction techniques used and compared are the Multiple linear regression, the Regression Trees and the Neural Network. To conclude the chapter, we compare the results of the three algorithms and conclude on the problem in question. In this chapter therefore, the analytics products being offered is to solve sales prediction problem for small retail business.· INTRODUCTION· PRACTICAL BUSINESS PROBLEM II (SALES PREDICTION)· MULTIPLE LINEAR REGRESSION· REGRESSIN TREES· NEURAL NETWORK (PREDICTION)· CONCLUSION ON SALES PREDICTION· PROBLEMS· REFERENCES CHAPTER 6: CLASSIFICATION TECHNIQUESIn this chapter, even though there are several classification techniques, we will explore the popular ones used for classification in the business domain. In doing this, we will use the third business problem centered on customer loyalty comparing neural network, classification tree and random forest algorithms. In solving this problem, we are particular about how to get and retain more customers for our small business. We will also introduce some other classification based techniques such as K-nearest neighbour logistic regression and persuasion modelling. We will use persuasion modelling for the fourth practical business problem. In using these techniques to solve the problem we explain the fundamental concepts in the chosen algorithms and use them to demonstrate how this problems solving process can be adopted in real business scenarios.· CLASSIFICATION MODELS & EVALUATION· PRACTICAL BUSINESS PROBLEM III (CUSTOMER LOYALTY)· NEURAL NETWORK· CLASSIFICATION TREE· RANDOM FOREST & BOOSTED TREES· K NEAREST NEIGHBOUR· LOGISTIC REGRESSION· PROBLEMS· REFERENCES CHAPTER 7: ADVANCED DESCRIPTIVE ANALYTICSThis chapter is focused mainly on advanced descriptive analytics techniques. In this chapter, we will first explain the concept of clustering which is a type of unsupervised learning approach. We will then pick one clustering technique which is the K means clustering. Using the fourth practical business problem, we will explain how we can use the K means clustering technique to solve a real business problem. Next will explain the association rule example and finally Network analysis. We conclude with the fifth business problem which is focused on using network analytics for employee efficiency.· CLUSTERING· K MEANS· PRACTICAL BUSINESS PROBLEM IV (Customer Segmentation)· ASSOCIATION ANALYSIS· NETWORK ANALYSIS· PRACTICAL BUSINESS PROBLEM V (Staff Efficiency)· PROBLEMS· REFERENCES CHAPTER 8: CASE STUDY PART IThis chapter is the beginning part of major consulting case study for this book. We will explain what transpired during a typical business analytics consulting and help to create a road map or an example of how to navigate a business analytics consulting project. We start with a description of the SME Ecommerce environment generally, since this is the business environment of our selected case study, we then talk about the sources of data for analytics peculiar this environment. Next we describe the business to be used as case study briefly, followed by the analytics road map peculiar to consulting for this business. This chapter ends with the results of the initial analysis and pre engagement phase which forms the bases for the detailed analytics and implementation phase in chapter 10.· SME ECORMERCE· INTRODUCTION TO SME CASE STUDY· INITIAL ANALYSIS· ANALYTICS APPROACH · PRE –ENGAGEMENT· PROBLEMS· REFERENCES CHAPTER 9: CASE STUDY PART IIIn this chapter, we will conclude the case study used for illustration of a typical business analytics consulting for an SME by presenting the details of the engagement phase for the case study in question. The post engagement phase is left out as the implementation of the recommendations is determined by the systems and procedures of the business. It is important to note that the consulting steps can be customized for any small business based on the intended problem. The whole steps described in chapter 9 and 10 have been made simple for understanding, though in real life business application there might be need to iterate the process until satisfactory results have been gotten. This is because you constantly need to incorporate feedback from the stakeholders and domain experts.· GOAL 1: INCREASE WEBSITE TRAFFIC· GOAL 2: INCREASE WEBSITE SALES REVENUE· PROBLEMS· REFERENCES

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Book SynopsisThe life cycle of companies and enterprises, at present, is short-lived due to rapid social and technological changes. Despite the growing awareness on the importance of knowledge management (KM) among academic researchers, it is still not widely practiced in industry. Why is this? Most KM programs emphasize the importance of capturing, retaining, and sharing organisational knowledge amongst their stakeholders. The beneficial effect of these programs is rarely felt immediately, which often results in senior management avoiding prioritising KM initiatives. To overcome this hurdle in implementing KM an approach that includes the assessment of knowledge risk factors and the disastrous effect on the daily operation of the company is explored. This book is the first attempt of its kind to provide a pragmatic view to launch knowledge risk management at the grassroot level, with steps by steps on what should be the mission and practical skills needed for a KM practitioner. Another surprise of this book is the numerous cases, examples and data that are brough about from the real business world. For business practitioners, KM researchers and those in HR, risk management, management accounting and Leadership this work is a must for expanding their understanding of Knowledge Management and knowledge risks.Table of ContentsChapter 1. IntroductionChapter 2. Assessment of Knowledge Risks Chapter 3. Intellectual Capital Charting, Accounting and Risks Chapter 4. Knowledge Audit Chapter 5. Knowledge Elicitation for Unstructured Business Process Chapter 6. Building a Learning Organization Chapter 7. KM Implementation Chapter 8. Measuring Corporate Performance

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Book SynopsisThis book constitutes the proceedings of the 8th International Symposium on Model-Based Safety and Assessment, IMBSA 2022, held in Munich, Germany, in September 2022. The 15 revised full papers and 3 short papers presented were carefully reviewed and selected from 27 initial submissions. The papers focus on model-based and automated ways of assessing safety and other attributes of dependability of complex systems. They are organized in topical sections on safety analysis automation, MBSA practices, causal models and failure modeling strategies, designing mitigations of faults and attacks, data based safety analysis, dynamic risk assessment.Table of ContentsSafety analysis automation.- An AEBS use case for Model-Based System Design integrating Safety Analyses and Simulation.- COMPASTA: Extending TASTE with formal design and verification functionality.- MBSA practices.- MBSA in aeronautics: a way to support safety activities.- Modeling the Variability of System Safety Analysis using State-Machine Diagrams.- Model-Based Safety Analysis: a Practical Experience.- Practical application of Model-Based Safety Analysis to the Design of Global Operating System of new rolling stock on automatic metro lines.- Plug-and-Produce... safely! End-to-End Model-Based Safety Assurance for Reconfigurable Industry 4.0.- Causal models and failure modeling strategies.- Strategies for modelling failure propagation in dynamic systems with AltaRica.- Towards Causal Model-based Engineering in Automotive System Safety.- Performance assessment of an offshore windmill farm using AltaRica 3.0.- Component Fault and Deficiency Tree (CFDT): Combining functional safety and SOTIF Analysis.- Designing mitigations of Faults and Attacks.- A Capella-based Tool for the Early Assessment of Nano/Micro Satellites Availability.- Data based safety analysis.- A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms.- Tool Paper: Time Series Anomaly Detection Platform for MATLAB Simulink.- Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring.- Dynamic risk assessment.- Engineering Dynamic Risk and Capability Models to Improve Cooperation Efficiency Between Human Workers and Autonomous Mobile Robots in Shared Spaces.- SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities.

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Book SynopsisThis textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples.Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology"This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at ChicagoTrade Review“I can strongly recommend this book to any graduate students who want to learn the theoretical parts of the broad area of data mining. It offers enough material for several semesters of data mining or machine learning courses. Researchers and practitioners who want to survey the principles and concepts of current data mining topics and learn their theoretical perspective would benefit greatly from this book.” (Daijin Ko, Mathematical Reviews, May, 2017)“Written by one of the most prodigious editors and authors in the data mining community, Data mining: the textbook is a comprehensive introduction to the fundamentals and applications of data mining. The recent drive in industry and academic toward data science and more specifically “big data” makes any well-written book on this topic a welcome addition to the bookshelves of experienced and aspiring data scientists… The writing style is excellent and the author managed to provide sufficient mathematical background in terms of formal proofs and notations, in order to make it self-contained and scientifically appealing to more theory-oriented readers.Covering more than 20 chapters and 700 pages, Aggarwal provides a unique textbook and reference to data mining, which I recommend to every reader working on or learning about data mining.” (Radu State, ACM Computing Reviews #CR143869)Table of ContentsIntroduction to Data Mining.- Data Preparation.- Similarity and Distances.- Association Pattern Mining.- Association Pattern Mining: Advanced Concepts.- Cluster Analysis.- Cluster Analysis: Advanced Concepts.- Outlier Analysis.- Outlier Analysis: Advanced Concepts.- Data Classification.- Data Classification: Advanced Concepts.- Mining Data Streams.- Mining Text Data.- Mining Time-Series Data.- Mining Discrete Sequences.- Mining Spatial Data.- Mining Graph Data.- Mining Web Data.- Social Network Analysis.- Privacy-Preserving Data Mining.

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Book SynopsisThis accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.Trade Review“This book contains a broad range of timely topics and presents interesting examples on real-life data using Python. … the book is a good addition to references on Python and data science. Students as well as practicing data scientists and engineers will benefit from the many techniques and use cases presented in the book.” (Computing Reviews, December, 2017)“The book ‘Introduction to Data Science’ is built as a starter presentation of concepts, techniques and approaches that constitute the initial contact with data science for scientists … . The style of the book recommends it to both undergraduates and postgraduates and the concluding remarks and references provide guidance for the next steps in the study of particular topics.” (Irina Ioana Mohorianu, zbMATH, Vol. 1365.62003, 2017)Table of ContentsIntroduction to Data Science Jordi Vitrià Toolboxes for Data Scientists Eloi Puertas and Francesc Dantí Descriptive statistics Petia Radeva and Laura Igual Statistical Inference Jordi Vitrià and Sergio Escalera Supervised Learning Oriol Pujol and Petia Radeva Regression Analysis Laura Igual and Jordi Vitrià Unsupervised Learning Petia Radeva and Oriol Pujol Network Analysis Laura Igual and Santi Seguí Recommender Systems Santi Seguí and Eloi Puertas Statistical Natural Language Processing for Sentiment Analysis Sergio Escalera and Santi Seguí Parallel Computing Francesc Dantí and Lluís Garrido

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Book SynopsisData matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases.Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today.By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.Trade Review"The book is very well organized and exceptionally well written. Because of the depth, amount, and quality of the material that is covered, I would expect this book to be one of the standard references in future years." William E. Winkler, U.S. Bureau of the Census, Washington, DC, USATable of ContentsPart I Overview.- Introduction.- The Data Matching Process.- Part II Steps of the Data Matching Process.- Data Pre-Processing.- Indexing.- Field and Record Comparison.- Classification.- Evaluation of Matching Quality and Complexity.- Part III Further Topics.- Privacy Aspects of Data Matching.- Further Topics and Research Directions.- Data Matching Systems.

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Book SynopsisAn expert system, also known as a knowledge based system, is a computer program that contains some of the subject-specific knowledge of one or more human experts. This class of program was first developed by researchers in artificial intelligence during the 1960s and 1970s and applied commercially throughout the 1980s. The most common form of expert systems is a program made up of a set of rules that analyse information usually supplied by the user of the system) about a specific class of problems, as well as providing mathematical analysis of the problem(s), and, depending upon their design, recommend a course of user action in order to implement corrections. It is a system that utilises what appear to be reasoning capabilities to reach conclusions. This book presents important research on in this dynamic field.

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Book SynopsisAn expert system, also known as a knowledge based system, is a computer program that contains some of the subject-specific knowledge of one or more human experts. This class of program was first developed by researchers in artificial intelligence during the 1960s and 1970s and applied commercially throughout the 1980s. The most common form of expert systems is a program made up of a set of rules that analyse information (usually supplied by the user of the system) about a specific class of problems, as well as providing mathematical analysis of the problem(s), and, depending upon their design, recommend a course of user action in order to implement corrections. It is a system that utilises what appear to be reasoning capabilities to reach conclusions. This volume presents important new research from around the globe.

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Book SynopsisLearn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) in writing regular expressions and other programmes. "How these tools can be both so very amazing in what they produce, and simultaneously so utterly doltish in their numerous failures, is the main thing this book tries to understand. For reasons I attempt to elucidate throughout, of all the domains of computer programming, games with regular expressions are particularly well suited for getting a grasp on the peculiar behaviors of AI." From the Preface For programmers of any experience level – no experience with AI coding tools is required. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On the one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which one makes the smartest use of lesser-known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the technology Ground-breaking large language model research from OpenAI, Google, Amazon, and others, have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions—a workhorse technology for developers used to describe, find, and manipulate patterns in the text? Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge?Trade Review"AI coding assistants are here, and they're transforming how programming is and will be done. If you know regular expressions, pick up this book and learn all about AI coding assistants. If you don't know regular expressions, well, pick it up anyway and experience how you learn with AI coding assistants." Dr. Daniel Zingaro University of Toronto, author of Algorithmic Thinking "I am a strong believer in Augmented Intelligence and welcome tools such as ChatGPT & Co-Pilot. To take meaningful steps toward Augmented Intelligence, we will need to understand both Humans' and Machines' strengths and weaknesses. This is where David's book comes in. Through the puzzles, David was able to show it well. Strongly recommended for anyone who is looking to use Artificial Intelligence for their business, to tap into its strength and prepare for potential risks." Koo Ping Shung, Data Science Rex

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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 SynopsisThis book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.Table of ContentsData Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - Clustering.

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Book SynopsisTable of Contents1. Introduction2. What is a Cognitive Device?3. Cognitive Devices as Human Assistants4. Cognitive Things in an Organization5. Reuse and Monetization6. Intelligent Observations7. Organization of Knowledge and Problem Solving8. Installation, Training, Maintenance, Security, and Infrastructure9. Machine-to-Machine Interfaces10. Man-to-Machine Interfaces11. Assisting in Human Communications12. Balance of Power and Societal Impacts

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Book Synopsis.NET Remoting.- Absolute Time.- Abstract Versus Concrete Temporal Query Languages.- Abstraction.- Access Control.- Access Control Administration Policies.- Access Control Policy Languages.- Access Path.- ACID Properties.- Active and Real-Time Data Warehousing.- Active Database Coupling Modes.- Active Database Execution Model.- Active Database Knowledge Model.- Active Database Management System Architecture.- Active Database Rulebase.- Active Database, Active Database (Management) System.- Active Storage.- Active XML.- Activity.- Activity Diagrams.- Actors/Agents/Roles.- Adaptive Interfaces.- Adaptive Middleware for Message Queuing Systems.- Adaptive Query Processing.- Adaptive Stream Processing.- ADBMS.- Administration Model for RBAC.- Administration Wizards.- Advanced Information Retrieval Measures.- Aggregation: Expressiveness and Containment.- Aggregation-Based Structured Text Retrieval.- Air Indexes for Spatial Databases.- AJAX.- Allen's Relations.- AMOSQL.- AMS Sketch.- Anchor TexTable of Contents.NET Remoting.- Absolute Time.- Abstract Versus Concrete Temporal Query Languages.- Abstraction.- Access Control.- Access Control Administration Policies.- Access Control Policy Languages.- Access Path.- ACID Properties.- Active and Real-Time Data Warehousing.- Active Database Coupling Modes.- Active Database Execution Model.- Active Database Knowledge Model.- Active Database Management System Architecture.- Active Database Rulebase.- Active Database, Active Database (Management) System.- Active Storage.- Active XML.- Activity.- Activity Diagrams.- Actors/Agents/Roles.- Adaptive Interfaces.- Adaptive Middleware for Message Queuing Systems.- Adaptive Query Processing.- Adaptive Stream Processing.- ADBMS.- Administration Model for RBAC.- Administration Wizards.- Advanced Information Retrieval Measures.- Aggregation: Expressiveness and Containment.- Aggregation-Based Structured Text Retrieval.- Air Indexes for Spatial Databases.- AJAX.- Allen's Relations.- AMOSQL.- AMS Sketch.- Anchor Text.- Annotation.- Annotation-based Image Retrieval.- Anomaly Detection on Streams.- Anonymity.- ANSI/INCITS RBAC Standard.- Answering Queries Using Views.- Anti-monotone Constraints.- Applicability Period.- Application Benchmark.- Application Recovery.- Application Server.- Application-Level Tuning.- Applications of Emerging Patterns for Microarray Gene Expression Data Analysis.- Applications of Sensor Network Data Management.- Approximate Queries in Peer-to-Peer Systems.- Approximate Query Processing.- Approximate Reasoning.- Approximation of Frequent Itemsets.- Apriori Property and Breadth-First Search Algorithms.- Architecture-Conscious Database System.- Archiving Experimental Data.- Armstrong Axioms.- Array Databases.- Array Databases_old.- Association Rule Mining on Streams.- Association Rules.- Asymmetric Encryption.- Atelic Data.- Atomic Event.- Atomicity.- Audio.- Audio Classification.- Audio Content Analysis.- Audio Metadata.- Audio Representation.- Audio Segmentation.- Auditing and Forensic Analysis.- Authentication.- Automatic Image Annotation.- Autonomous Replication.- Average Precision.- Average Precision at n.- Average Precision Histogram.- Average R-Precision.- B+-Tree.- Backup and Restore.- Bag Semantics.- Bagging.- Bayesian Classification.- Benchmark Frameworks.- Benchmarks for Big Data Analytics.- Big Data Platforms for Data Analytics.- Big Stream Systems.- Biological Metadata Management.- Biological Networks.- Biological Resource Discovery.- Biological Sequences.- Biomedical Data/Content Acquisition, Curation.- Biomedical Image Data Types and Processing.- Biomedical Scientific Textual Data Types and Processing.- Biostatistics and Data Analysis.- Bi-Temporal Indexing.- Bitemporal Interval.- Bitemporal Relation.- Bitmap Index.- Bitmap-based Index Structures.- Blind Signatures.- Bloom Filters.- BM25.- Boolean Model.- Boosting.- Bootstrap.- Boyce-Codd Normal Form.- BP-Completeness.- Bpref.- Browsing.- Browsing in Digital Libraries.- B-Tree Locking.- Buffer Management.- Buffer Manager.- Buffer Pool.- Business Intelligence.- Business Process Execution Language.- Business Process Management.- Business Process Modeling Notation.- Business Process Reengineering.- Cache-Conscious Query Processing.- Calendar.- Calendric System.- CAP Theorem.- Cardinal Direction Relationships.- Cartesian Product.- Cataloging in Digital Libraries.- Causal Consistency.- Certain (and Possible) Answers.- Change Detection on Streams.- Channel-Based Publish/Subscribe.- Chart.- Chase.- Checksum and Cyclic Redundancy Check Mechanism.- Choreography.- Chronon.- Citation.- Classification.- Classification by Association Rule Analysis.- Classification in Streams.- Client-Server Architecture.- Clinical Data Acquisition, Storage and Management.- Clinical Data and Information Models.- Clinical Data Quality and Validation.- Clinical Decision Support.- Clinical Document Architecture.- Clinical Event.- Clinical Knowledge Repository.- Clinical Observation.- Clinical Ontologies.- Clinical Order.- Closed Itemset Mining and Non-redundant Association Rule Mining.- Closest-Pair Query.- Cloud Computing.- Cloud Intelligence.- Cluster and Distance Measure.- Clustering for Post Hoc Information Retrieval.- Clustering on Streams.- Clustering Overview and Applications.- Clustering Validity.- Clustering with Constraints.- Collaborative Filtering.- Column Segmentation.- Column Stores.- Common Warehouse Metamodel.- Comparative Visualization.- Compensating Transactions.- Complex Event.- Complex Event Processing.- Composed Services and WS-BPEL.- Composite Event.- Composition.- Comprehensions.- Compression of Mobile Location Data.- Computational Media Aesthetics.- Computationally Complete Relational Query Languages.- Computerized Physician Order Entry.- Conceptual Modeling Foundations.- Conceptual Schema Design.- Concurrency Control - Traditional Approaches.- Concurrency Control for Replicated Databases.- Concurrency Control Manager.- Conditional Tables.- Conjunctive Query.- Connection.- Consistency Models For Replicated Data.- Consistent Query Answering.- Constraint Databases.- Constraint Query Languages.- Constraint-Driven Database Repair.- Content-and-Structure Query.- Content-Based Publish/Subscribe.- Content-Based Video Retrieval.- Content-Only Query.- Context.- Contextualization in Structured Text Retrieval.- Continuous Data Protection.- Continuous Monitoring of Spatial Queries.- Continuous Multimedia Data Retrieval.- Continuous Queries in Sensor Networks.- Continuous Query.- ConTract.- Control Data.- Convertible Constraints.- Coordination.- Copyright Issues in Databases.- CORBA.- Correctness Criteria Beyond Serializability.- Cost and quality trade-offs in crowdsourcing.- Cost Estimation.- Count-Min Sketch.- Coupling and De-coupling.- Covering Index.- Crash Recovery.- Cross-Language Mining and Retrieval.- Cross-Modal Multimedia Information Retrieval.- Cross-Validation.- Crowd Database Operators.- Crowd Database Systems.- Crowd Mining and Analysis.- Crowdsourcing Geographic Information Systems.- Cube.- Cube Implementations.- Current Semantics.- Curse of Dimensionality.- Daplex.- Data Acquisition and Dissemination in Sensor Networks.- Data Aggregation in Sensor Networks.- Data Broadcasting, Caching and Replication in Mobile Computing.- Data Cleaning.- Data Compression in Sensor Networks.- Data Conflicts.- Data Definition.- Data Definition Language (DDL).- Data Dictionary.- Data Encryption.- Data Estimation in Sensor Networks.- Data Exchange.- Data Fusion.- Data Fusion in Sensor Networks.- Data Generation.- Data Governance.- Data Integration Architectures and Methodology for the Life Sciences.- Data Integration in Web Data Extraction System.- Data Management for VANETs.- Data Management Fundamentals: Database Management System.- Data Management in Data Centers.- Data Manipulation.- Data Manipulation Language (DML).- Data Mart.- Data Migration Management.- Data Mining.- Data Partitioning.- Data Privacy and Patient Consent.- Data Profiling.- Data Provenance.- Data Quality Assessment.- Data Quality Dimensions.- Data Quality Models.- Data Rank/Swapping.- Data Reduction.- Data Replication.- Data Sampling.- Data Scrubbing.- Data Sketch/Synopsis.- Data Skew.- Data Storage and Indexing in Sensor Networks.- Data Stream.- Data Stream Management Architectures and Prototypes.- Data Types in Scientific Data Management.- Data Uncertainty Management in Sensor Networks.- Data Visualization.- Data Warehouse.- Data Warehouse Life-Cycle and Design.- Data Warehouse Maintenance, Evolution and Versioning.- Data Warehouse Metadata.- Data Warehouse Security.- Data Warehousing for Clinical Research.- Data Warehousing in Cloud Environments.- Data Warehousing on Non-Conventional Data.- Data Warehousing Systems: Foundations and Architectures.- Data, Text, and Web Mining in Healthcare.- Database.- Database Adapter and Connector.- Database Administrator (DBA).- Database Appliances.- Database Benchmarks.- Database Clustering Methods.- Database Clusters.- Database Dependencies.- Database Design.- Database Languages for Sensor Networks.- Database Machine.- Database Management System.- Database Middleware.- Database Repair.- Database Reverse Engineering.- Database Schema.- Database Security.- Database System.- Database Techniques to Improve Scientific Simulations.- Database Trigger.- Database Tuning using Combinatorial Search.- Database Tuning using Online Algorithms.- Database Tuning using Trade-off Elimination.- Database Use in Science Applications.- Datalog.- DBMS Component.- DBMS Interface.- DCE.- DCOM.- Decay Models.- Decision Rule Mining in Rough Set Theory.- Decision Tree Classification.- Decision Trees.- Declarative Networking.- Deductive Data Mining using Granular Computing.- Deduplication.- Deduplication in Data Cleaning.- Deep Instantiation.- Deep-Web Search.- Dense Index.- Dense Pixel Displays.- Density-based Clustering.- Description Logics.- Design for Data Quality.- Dewey Decimal System.- Diagram.- Difference.- Differential Privacy.- Digital Archives and Preservation.- Digital Curation.- Digital Elevation Models.- Digital Libraries.- Digital Rights Management.- Digital Signatures.- Dimension.- Dimension Reduction Techniques for Clustering.- Dimensionality Reduction.- Dimensionality Reduction Techniques For Nearest Neighbor Computations.- Dimension-Extended Topological Relationships.- Direct Attached Storage.- Direct Manipulation.- Disaster Recovery.- Disclosure Risk.- Discounted Cumulated Gain.- Discovery.- Discrete Wavelet Transform and Wavelet Synopses.- Discretionary Access Control.- Disk.- Disk Power Saving.- Distortion Techniques.- Distributed Architecture.- Distributed Concurrency Control.- Distributed Data Streams.- Distributed Database Design.- Distributed Database Systems.- Distributed DBMS.- Distributed Deadlock Management.- Distributed File Systems.- Distributed Hash Table.- Distributed Join.- Distributed Machine Learning.- Distributed Query Optimization.- Distributed Query Processing.- Distributed Recovery.- Distributed Spatial Databases.- Distributed Transaction Management.- Divergence from Randomness Models.- D-measure.- Document.- Document Clustering.- Document Databases.- Document Field.- Document Length Normalization.- Document Links and Hyperlinks.- Document Representations (Inclusive Native and Relational).- Dublin Core.- Dynamic Graphics.- Dynamic Web Pages.- eAccessibility.- ECA Rule Action.- ECA Rule Condition.- ECA Rules.- e-Commerce Transactions.- Effectiveness Involving Multiple Queries.- Ehrenfeucht-Fraïssé Games.- Elasticity.- Electronic Dictionary.- Electronic Encyclopedia.- Electronic Health Record.- Electronic Ink Indexing.- Electronic Newspapers.- Eleven Point Precision-recall Curve.- Emergent Semantics.- Emerging Pattern Based Classification.- Emerging Patterns.- Energy Efficiency in Data Centers.- Ensemble.- Enterprise Application Integration.- Enterprise Content Management.- Enterprise Service Bus.- Enterprise Terminology Services.- Entity Relationship Model.- Entity Resolution.- Entity Retrieval.- Equality-Generating Dependencies.- ERR- Expected Reciprocal Rank.- ERR-IA Intent-aware ERR.- Escrow Transactions.- European Law in Databases.- Evaluation Metrics for Structured Text Retrieval.- Evaluation of Relational Operators.- Event.- Event and Pattern Detection over Streams.- Event Causality.- Event Channel.- Event Cloud.- Event Detection.- Event Driven Architecture.- Event Flow.- Event in Active Databases.- Event in Temporal Databases.- Event Lineage.- Event Pattern Detection.- Event Prediction.- Event Processing Agent.- Event Processing Network.- Event Sink.- Event Source.- Event Specification.- Event Stream.- Event Transformation.- Event-Driven Business Process Management.- Eventual Consistency.- Evidence Based Medicine.- Executable Knowledge.- Execution Skew.- Explicit Event.- Exploratory Data Analysis.- Expressive Power of Query Languages.- Extended Entity-Relationship Model.- Extended Transaction Models and the ACTA Framework.- Extendible Hashing.- Extraction, Transformation, and Loading.- Faceted Search.- Fault-Tolerance and High Availability in Data Stream Management Systems.- Feature Extraction for Content-Based Image Retrieval.- Feature Selection for Clustering.- Feature-Based 3D Object Retrieval.- Field-Based Information Retrieval Models.- Field-Based Spatial Modeling.- First-Order Logic: Semantics.- First-Order Logic: Syntax.- Fixed Time Span.- Flex Transactions.- FM Synopsis.- F-Measure.- Focused Web Crawling.- FOL Modeling of Integrity Constraints (Dependencies).- Forever.- Form.- Fourth Normal Form.- FQL.- Fractal.- Frequency Moments.- Frequent Graph Patterns.- Frequent Items on Streams.- Frequent Itemset Mining with Constraints.- Frequent Itemsets and Association Rules.- Frequent Partial Orders.- Fully-Automatic Web Data Extraction.- Functional Data Model.- Functional Dependencies for Semi-Structured Data.- Functional Dependency.- Functional Query Language.- Fuzzy Models.- Fuzzy Relation.- Fuzzy Set.- Fuzzy Set Approach.- Fuzzy/Linguistic IF-THEN Rules and Linguistic Descriptions.- Gazetteers.- Gene Expression Arrays.- Generalization of ACID Properties.- Generalized Search Tree.- Genetic Algorithms.- Geographic Information System.- Geographical Information Retrieval.- Geography Markup Language.- Geometric Stream Mining.- GEO-RBAC Model.- Georeferencing.- Geosocial Networks.- Geospatial Metadata.- Geo-Targeted Web Search.- GMAP.- Grammar Inference.- Graph.- Graph Data Management in Scientific Applications.- Graph Database.- Graph Management in the Life Sciences.- Graph Mining.- Graph Mining on Streams.- Graph OLAP.- Graphical Models for Uncertain Data Management.- Grid and Workflows.- Grid File (and Family).- GUIs for Web Data Extraction.- Hash Functions.- Hash Join.- Hash-based Indexing.- Healthcare Metrics.- Hierarchial Clustering.- Hierarchical Data Model.- Hierarchical Data Summarization.- Hierarchical Heavy Hitter Mining on Streams.- Hierarchy.- High Dimensional Indexing.- Histogram.- Histograms on Streams.- History in Temporal Databases.- Homomorphic Encryption.- Horizontally Partitioned Data.- Human Factors Modeling in Crowdsourcing.- Human-centered Computing: Application to Multimedia.- Human-Computer Interaction.- Hypertexts.- I/O Model of Computation.- Icon.- Iconic Displays.- Image.- Image Content Modeling.- Image Database.- Image Management for Biological Data.- Image Metadata.- Image Querying.- Image Representation.- Image Retrieval and Relevance Feedback.- Image Segmentation.- Image Similarity.- Implementation of Database Operators (Joins, Group by, etc.).- Implication of Constraints.- Implications of Genomics for Clinical Informatics.- Implicit Event.- Incomplete Information.- Inconsistent Databases.- Incremental Computation of Queries.- Incremental Crawling.- Incremental Maintenance of Views with Aggregates.- Index Creation and File Structures.- Index Join.- Index Structures for Biological Sequences.- Index Tuning.- Indexed Sequential Access Method.- Indexing and Similarity Search.- Indexing Compressed Text.- Indexing Historical Spatio-Temporal Data.- Indexing in pub/sub systems.- Indexing Metric Spaces.- Indexing of Data Warehouses.- Indexing of the Current and Near-Future Positions of Moving Objects.- Indexing Techniques for Multimedia Data Retrieval.- Indexing the Web.- Indexing Uncertain Data.- Indexing Units of Structured Text Retrieval.- Indexing with Crowds.- Individually Identifiable Data.- Inference Control in Statistical Databases.- Information Extraction.- Information Filtering.- Information Foraging.- Information Integration.- Information Integration Techniques for Scientific Data.- Information Lifecycle Management.- Information Loss Measures.- Information Navigation.- Information Quality.- Information Quality and Decision Making.- Information Quality Assessment.- Information Quality Policy and Strategy.- Information Quality: Managing Information as a Product.- Information Retrieval.- Information Retrieval Models.- Information Retrieval Operations.- Infrastructure As-A-Service (IaaS).- Initiative for the Evaluation of XML Retrieval.- Initiator.- In-Network Query Processing.- Integrated DB and IR Approaches.- Integration of Rules and Ontologies.- Intelligent Storage Systems.- Interactive Analytics in Social Media.- Interface.- Interface Engines in Healthcare.- Interoperability in Data Warehouses.- Interoperation of NLP-based Systems with Clinical Databases.- Inter-Operator Parallelism.- Inter-Query Parallelism.- Intra-operator Parallelism.- Intra-Query Parallelism.- Intrusion Detection Technology.- Inverse Document Frequency.- Inverted Files.- IP Storage.- Iterator.- Java Database Connectivity.- Java Enterprise Edition.- Java Metadata Facility.- Join.- Join Dependency.- Join Index.- Join Order.- k-Anonymity.- Karp-Luby Sampling.- KDD Pipeline.- Key.- K-Means and K-Medoids.- Knowledge Base.- Knowledge Base Extraction.- Language Models.- Languages for Web Data Extraction.- Learning Distance Measures.- Lexical Analysis of Textual Data.- Licensing and Contracting Issues in Databases.- Lifespan.- Lightweight Ontologies.- Linear Hashing.- Linear Regression.- Linked Open Data.- Linking and Brushing.- Load Balancing in Peer-to-Peer Overlay Networks.- Load Shedding.- LOC METS.- Locality.- Locality of Queries.- Location Based Recommendation.- Location Management in Mobile Environments.- Location Update Management.- Location-Based Services.- Locking Granularity and Lock Types.- Logging and Recovery.- Logging/Recovery Subsystem.- Logical and Physical Data Independence.- Logical Database Design: from Conceptual to Logical Schema.- Logical Document Structure.- Logical Foundations of Web Data Extraction.- Logical Models of Information Retrieval.- Logical Unit Number.- Logical Unit Number Mapping.- Logical Volume Manager.- Log-Linear Regression.- Loop.- Loose Coupling.- Machine Learning in Computational Biology.- Main Memory.- Main Memory DBMS.- Maintenance of Materialized Views with Outer-Joins.- Maintenance of Recursive Views.- Managing Compressed Structured Text.- Managing Data Integration Uncertainty.- Managing Probabilistic Entity Extraction.- Mandatory Access Control.- MANET Databases.- MAP.- Map Matching.- MapReduce.- Markup Language.- MashUp.- Massive Array of Idle Disks.- Matrix Masking.- Max-Pattern Mining.- Mean Reciprocal Rank.- Measure.- Mediation.- Membership Query.- Memory Hierarchy.- Memory Locality.- Merkle Trees.- Message Authentication Codes.- Message Queuing Systems.- Meta Data Repository.- Meta Object Facility.- Metadata.- Metadata Interchange Specification.- Metadata Registry, ISO/IEC 11179.- Metamodel.- Metasearch Engines.- Metric Space.- Microaggregation.- Microbenchmark.- Microdata.- Microdata Rounding.- Middleware Support for Database Replication and Caching.- Middleware Support for Precise Failure Semantics.- Mining of Chemical Data.- Mobile Database.- Mobile Interfaces.- Mobile resource search.- Mobile Sensor Network Data Management.- Model Management.- Model-based Querying in Sensor Networks.- Monotone Constraints.- Monte Carlo Methods for Uncertain Data.- Moving Object.- Moving Objects Databases and Tracking.- MRR.- Multi-Data Center Consistency Properties.- Multi-Data Center Replication Protocols.- Multidimensional Data Formats.- Multidimensional Modeling.- Multidimensional Scaling.- Multi-Level Modeling.- Multi-Level Recovery and the ARIES Algorithm.- Multilevel Secure Database Management System.- Multilevel Transactions and Object-Model Transactions.- Multimedia Data.- Multimedia Data Buffering.- Multimedia Data Indexing.- Multimedia Data Querying.- Multimedia Data Storage.- Multimedia Databases.- Multimedia Information Retrieval Model.- Multimedia Metadata.- Multimedia Presentation Databases.- Multimedia Resource Scheduling.- Multimedia Retrieval Evaluation.- Multimedia Tagging.- Multimodal Interfaces.- Multi-Pathing.- Multiple Representation Modeling.- Multi-Query Optimization.- Multi-Resolution Terrain Modeling.- Multi-Step Query Processing.- Multitenancy.- Multi-Tier Architecture.- Multi-tier Storage Systems.- Multivalued Dependency.- Multivariate Visualization Methods.- Multi-version Serializability and Concurrency Control.- Naive Tables.- Narrowed Extended XPath I.- Natural Interaction.- Near-duplicate Retrieval.- Nearest Neighbor Classification.- Nearest Neighbor Query.- Nearest Neighbor Query in Spatio-temporal Databases.- Nested Loop Join.- Nested Transaction Models.- Network Attached Secure Device.- Network Attached Storage.- Network Data Model.- Neural Networks.- N-Gram Models.- Noise Addition.- Nonparametric Data Reduction Techniques.- Non-Perturbative Masking Methods.- Non-relational Streams.- Nonsequenced Semantics.- Normal Form ORA-SS Schema Diagrams.- Normal Forms and Normalization.- NoSQL Stores.- Now in Temporal Databases.- Null Values.- OASIS.- Object Constraint Language.- Object Data Models.- Object Identity.- Object Recognition.- Object Relationship Attribute Data Model for Semi-structured Data.- Object Storage Protocol.- Object-Role Modeling.- OLAM.- OLAP Personalization and Recommendation.- OLAP Personalization and Recommendation_old.- One-Copy-Serializability.- One-Pass Algorithm.- On-Line Analytical Processing.- Online Recovery in Parallel Database Systems.- Ontologies and Life Science Data Management.- Ontology.- Ontology Elicitation.- Ontology Engineering.- Ontology Visual Querying.- Ontology-Based Data Access and Integration.- Open Database Connectivity.- Open Information Extraction.- Open Nested Transaction Models.- Operator-Level Parallelism.- Opinion Mining.- Optimistic Replication and Resolution.- Optimization and Tuning in Data Warehouses.- OQL.- Orchestration.- Order Dependency.- OR-Join.- OR-Split.- OSQL.- Outlier Detection.- Overlay Network.- OWL: Web Ontology Language.- P/FDM.- Parallel and Distributed Data Warehouses.- Parallel Coordinates.- Parallel Data Placement.- Parallel Database Management.- Parallel Hash Join, Parallel Merge Join, Parallel Nested Loops Join.- Parallel Query Execution Algorithms.- Parallel Query Optimization.- Parallel Query Processing.- Parameterized Complexity of Queries.- Parametric Data Reduction Techniques.- Partial Replication.- Path Query.- Pattern-Growth Methods.- Peer Data Management System.- Peer to Peer Overlay Networks: Structure, Routing and Maintenance.- Peer-To-Peer Content Distribution.- Peer-to-Peer Data Integration.- Peer-to-Peer Publish-Subscribe Systems.- Peer-to-Peer Storage.- Peer-to-Peer System.- Peer-to-Peer Web Search.- Performance Analysis of Transaction Processing Systems.- Performance Monitoring Tools.- Period-Stamped Temporal Models.- Personalized Web Search.- Petri Nets.- Physical Clock.- Physical Database Design for Relational Databases.- Physical Layer Tuning.- Pipeline.- Pipelining.- Platform As-A-Service (PaaS).- Point-in-Time Copy.- Point-Stamped Temporal Models.- Polytransactions.- Positive Relational Algebra.- Possible Answers.- PRAM.- Precision.- Precision and Recall.- Precision at n.- Precision-Oriented Effectiveness Measures.- Predictive Analytics.- Preference Queries.- Preference Specification.- Prescriptive Analytics.- Presenting Structured Text Retrieval Results.- Primary Index.- Principal Component Analysis.- Privacy.- Privacy Metrics.- Privacy Policies and Preferences.- Privacy through Accountability.- Privacy-Enhancing Technologies.- Privacy-Preserving Data Mining.- Privacy-Preserving DBMSs.- Private Information Retrieval.- Probabilistic Databases.- Probabilistic Entity Resolution.- Probabilistic Retrieval Models and Binary Independence Retrieval (BIR) Model.- Probabilistic Skylines.- Probabilistic Spatial Queries.- Probabilistic Temporal Databases.- Probability Ranking Principle.- Probability Smoothing.- Process Life Cycle.- Process Mining.- Process Modeling.- Process Optimization.- Process Structure of a DBMS.- Processing Overlaps in Structured Text Retrieval.- Processing Structural Constraints.- Processor Cache.- Profiles and Context for Structured Text Retrieval.- Projection.- Propagation-based Structured Text Retrieval.- Protection from Insider Threats.- Provenance.- Provenance and Reproducibility.- Provenance in Databases.- Provenance in Scientific Databases.- Provenance in Workflows.- Provenance Management.- Provenance Standards.- Provenance Storage.- Provenance: Privacy and Security.- Pseudonymity.- Publish/Subscribe.- Publish/Subscribe over Streams.- Punctuations.- Q-measure.- Quadtrees (and Family).- Qualitative Temporal Reasoning.- Quality and Trust of Information Content and Credentialing.- Quality of Data Warehouses.- Quantiles on Streams.- Quantitative Association Rules.- QUEL.- Query by Humming.- Query Containment.- Query Evaluation Techniques for Multidimensional Data.- Query Expansion for Information Retrieval.- Query Expansion Models.- Query Language.- Query Languages and Evaluation Techniques for Biological Sequence Data.- Query Languages for the Life Sciences.- Query Load Balancing in Parallel Database Systems.- Query Optimization.- Query Optimization (in Relational Databases).- Query Optimization in Sensor Networks.- Query Plan.- Query Point Movement Techniques for Content-Based Image Retrieval.- Query Processing.- Query Processing (in Relational Databases).- Query Processing and Optimization in Object Relational Databases.- Query Processing in data integration systems.- Query Processing in Data Warehouses.- Query Processing in Deductive Databases.- Query Processing over Uncertain Data.- Query Processor.- Query Rewriting.- Query Rewriting Using Views.- Query Translation.- Quorum Systems.- Randomization Methods to Ensure Data Privacy.- Range Query.- Rank-aware Query Processing.- Ranked XML Processing.- Ranking Functions.- Ranking Views.- Rank-Join.- Rank-Join Indices.- Raster Data Management and Multi-Dimensional Arrays.- RDF Stores.- RDF Technology.- Real and Synthetic Test Datasets.- Real-Time Transaction Processing.- Recall.- Receiver Operating Characteristic.- Recommender Systems.- Record Linkage.- Record Matching.- Redundant Arrays of Independent Disks.- Reference Knowledge.- Region Algebra.- Regulatory Compliance in Data Management.- Relational Algebra.- Relational Calculus.- Relational Model.- Relationships in Structured Text Retrieval.- Relative Time.- Relevance.- Relevance Feedback.- Relevance Feedback for Content-Based Information Retrieval.- Relevance Feedback for Text Retrieval.- Replica Control.- Replica Freshness.- Replicated Data Types.- Replicated Database Concurrency Control.- Replication.- Replication Based on Group Communication.- Replication for Availability and Fault-Tolerance.- Replication for High Availability.- Replication for Paxos.- Replication for Scalability.- Replication in Multi-Tier Architectures.- Replication with Snapshot Isolation.- Reputation and Trust.- Request Broker.- Residuated Lattice.- Resource Allocation Problems in Spatial Databases.- Resource Description Framework.- Resource Description Framework (RDF) Schema (RDFS).- Resource Identifier.- Result Display.- Retrospective Event Processing.- Reverse Nearest Neighbor Query.- Reverse Top-k Queries.- Rewriting Queries using Views.- RMI.- Road Networks.- Rocchio's Formula.- Role Based Access Control.- R-Precision.- R-Tree (and Family).- Rule-based Classification.- Safety and Domain Independence.- Sagas.- Sampling Techniques for Statistical Databases.- SAN File System.- Scalable Decision Tree Construction.- Scheduler.- Scheduling Strategies for Data Stream Processing.- Schema Evolution.- Schema Mapping.- Schema Mapping Composition.- Schema Matching.- Schema Tuning.- Schema Versioning.- Scheme/Ontology Extraction.- Scientific Databases.- Scientific Visualization.- Scientific Workflows.- Score Aggregation.- Screen Scraper.- SCSI Target.- SDC Score.- Search Engine Metrics.- Searching Digital Libraries.- Second Normal Form (2NF).- Secondary Index.- Secure Data Outsourcing.- Secure Database Development.- Secure Multiparty Computation Methods.- Secure Transaction Processing.- Security Services.- Segmentation and Stratification.- Segmentation and Stratification_old.- Selection.- Selectivity Estimation.- Self-Maintenance of Views.- Self-Management Technology in Databases.- Semantic Atomicity.- Semantic Crowd Sourcing.- Semantic Data Integration for Life Science Entities.- Semantic Data Model.- Semantic Matching.- Semantic Modeling and Knowledge Representation for Multimedia Data.- Semantic Modeling for Geographic Information Systems.- Semantic Overlay Networks.- Semantic Social Web.- Semantic Streams.- Semantic Web.- Semantic Web Query Languages.- Semantic Web Services.- Semantics-based Concurrency Control.- Semijoin.- Semijoin Program.- Semi-Structured Data.- Semi-Structured Data Model.- Semi-Structured Database Design.- Semi-Structured Query Languages.- Semi-Supervised Learning.- Sensor Networks.- Sequenced Semantics.- Sequential Patterns.- Serializability.- Serializable Snapshot Isolation.- Service Component Architecture (SCA).- Service Oriented Architecture.- Session.- Shared-Disk Architecture.- Shared-Memory Architecture.- Shared-Nothing Architecture.- Side-Effect-Free View Updates.- Signature Files.- Similarity and Ranking Operations.- Simplicial Complex.- Singular Value Decomposition.- Skyline Queries and Pareto Optimality.- Snapshot Equivalence.- Snapshot Isolation.- Snippet.- Snowflake Schema.- SOAP.- Social Applications.- Social influence.- Social Media Analysis.- Social Media Analytics.- Social Media Harvesting.- Social network analysis.- Social Networks.- Software As-A-Service (SaaS).- Software Transactional Memory.- Software-Defined Storage.- Solid State Drive (SSD).- Sort-Merge Join.- Space-Filling Curves.- Space-Filling Curves for Query Processing.- SPARQL.- Sparse Index.- Spatial and Spatio-Temporal Data Models and Languages.- Spatial and Temporal Data Warehouses .- Spatial Anonymity.- Spatial Data Analysis.- Spatial Data Mining.- Spatial Data Types.- Spatial Datawarehousing.- Spatial Indexing Techniques.- Spatial Join.- Spatial Keyword Search.- Spatial Matching Problems.- Spatial Network Databases.- Spatial Operations and Map Operations.- Spatial Queries in the Cloud.- Spatio-Temporal Data Mining.- Spatio-Temporal Data Types.- Spatio-Temporal Data Warehouses.- Spatiotemporal Interpolation Algorithms.- Spatio-Temporal Selectivity Estimation.- Spatio-Temporal Trajectories.- Specialization and Generalization.- Specificity.- Spectral Clustering.- Split.- Split Transactions.- SQL.- SQL Analytics on Big Data.- SQL Isolation Levels.- SQL-Based Temporal Query Languages.- Stable Distribution.- Stack-based Query Language.- Staged DBMS.- Standard Effectiveness Measures.- Star Index.- Star Schema.- State-based Publish/Subscribe.- Statistical Data Management.- Statistical Disclosure Limitation For Data Access.- Steganography.- Stemming.- Stop-&-go Operator.- Stoplists.- Storage Access Models.- Storage Area Network.- Storage Consolidation.- Storage Devices.- Storage Grid.- Storage Management.- Storage Management Initiative-Specification.- Storage Manager.- Storage Network Architectures.- Storage Networking Industry Association.- Storage of Large Scale Multidimensional Data.- Storage Power Management.- Storage Protection.- Storage Protocols.- Storage Resource Management.- Storage Security.- Storage Virtualization.- Stored Procedure.- Stream Mining.- Stream Models.- Stream Processing.- Stream processing on modern hardware.- Stream Reasoning.- Stream Sampling.- Stream Similarity Mining.- Streaming Analytics.- Streaming Applications.- Stream-Oriented Query Languages and Operators.- Strong Consistency Models for Replicated Data.- Structural Indexing.- Structure Analytics in Social Media.- Structure Weight.- Structured Data in Peer-to-Peer Systems.- Structured Document Retrieval.- Structured Text Retrieval Models.- Subject Spaces.- Subspace Clustering Techniques.- Success at n.- Succinct Constraints.- Suffix Tree.- Summarizability.- Summarization.- Support Vector Machine.- Supporting Transaction Time Databases.- Symbolic Representation.- Symmetric Encryption.- Synopsis Structure.- Synthetic Microdata.- System R (R*) Optimizer.- Table.- Tabular Data.- Taxonomy: Biomedical Health Informatics.- tBench.- Telic Distinction in Temporal Databases.- Telos.- Temporal Access Control.- Temporal Aggregation.- Temporal Algebras.- Temporal Analytics in Social Media.- Temporal Benchmarks.- Temporal Coalescing.- Temporal Compatibility.- Temporal Conceptual Models.- Temporal Constraints.- Temporal Data Mining.- Temporal Data Models.- Temporal Database.- Temporal Datawarehousing.- Temporal Dependencies.- Temporal Element.- Temporal Expression.- Temporal Generalization.- Temporal Granularity.- Temporal Homogeneity.- Temporal Indeterminacy.- Temporal Integrity Constraints.- Temporal Joins.- Temporal Logic in Database Query Languages.- Temporal Logical Models.- Temporal Object-Oriented Databases.- Temporal Periodicity.- Temporal Projection.- Temporal PSM.- Temporal Query Languages.- Temporal Query Processing.- Temporal Relational Calculus.- Temporal Specialization.- Temporal Strata.- Temporal Support in the SQL Standard.- Temporal Vacuuming.- Temporal Visual Languages.- Temporal XML.- Term Proximity.- Term Statistics for Structured Text Retrieval.- Term Weighting.- Test Collection.- Text Analytics.- Text Analytics in Social Media.- Text Categorization.- Text Clustering.- Text Compression.- Text Generation.- Text Index Compression.- Text Indexing and Retrieval.- Text Indexing Techniques.- Text Mining.- Text Mining of Biological Resources.- Text Representation.- Text Segmentation.- Text Semantic Representation.- Text Stream Processing.- Text Streaming Model.- Text Summarization.- Text Visualization.- TF*IDF.- Thematic Map.- Third Normal Form.- Three-Dimensional GIS and Geological Applications.- Three-Phase Commit.- Tight Coupling.- Time Aggregated Graphs.- Time and Information Retrieval.- Time Domain.- Time in Philosophical Logic.- Time Instant.- Time Interval.- Time Period.- Time Series Query.- Time Span.- Time-Line Clock.- Timeslice Operator.- Topic Detection and Tracking.- Topic Maps.- Topic-based Publish/Subscribe.- Top-k Queries.- Top-K Selection Queries on Multimedia Datasets.- Topological Data Models.- Topological Relationships.- Trajectory.- Transaction.- Transaction Chopping.- Transaction Management.- Transaction Manager.- Transaction Models - the Read/Write Approach.- Transaction Time.- Transactional Middleware.- Transactional Processes.- Transactional Stream Processing.- Transaction-Time Indexing.- Tree-based Indexing.- Treemaps.- Triangular Norms.- Triangulated Irregular Network.- Trie.- Trip Planning Queries.- Trust and Reputation in Peer-to-Peer Systems.- Trust in Blogosphere.- Trusted Hardware.- TSQL2.- Tuning Concurrency Control.- Tuple-Generating Dependencies.- Two-Dimensional Shape Retrieval.- Two-Phase Commit.- Two-Phase Commit Protocol.- Two-Phase Locking.- Two-Poisson model.- Type-based Publish/Subscribe.- U-measure.- Uncertain Data Lineage.- Uncertain Data Mining.- Uncertain Data Models.- Uncertain Data Streams.- Uncertain Data Summarization.- Uncertain Graph Data Management.- Uncertain Spatial Data Management.- Uncertain Top-k Queries.- Uncertainty in Events.- Uncertainty Management in Scientific Database Systems.- Unicode.- Unified Modeling Language.- Union.- Unobservability.- Updates and Transactions in Peer-to-Peer Systems.- Updates through Views.- Usability.- User-Defined Time.- Valid Time.- Valid-Time Indexing.- Value Equivalence.- Variable Time Span.- Vector-Space Model.- Vertically Partitioned Data.- Video.- Video Content Analysis.- Video Content Modeling.- Video Content Structure.- Video Metadata.- Video Querying.- Video Representation.- Video Scene and Event Detection.- Video Segmentation.- Video Sequence Indexing.- Video Shot Detection.- Video Summarization.- View Adaptation.- View Definition.- View Maintenance.- View Maintenance Aspects.- View-based Data Integration.- Views.- Virtual Partitioning.- Visual Analytics.- Visual Association Rules.- Visual Classification.- Visual Clustering.- Visual Content Analysis.- Visual Data Mining.- Visual Formalisms.- Visual Interaction.- Visual Interfaces.- Visual Interfaces for Geographic Data.- Visual interfaces for streaming data.- Visual Metaphor.- Visual On-Line Analytical Processing (OLAP).- Visual Perception.- Visual Query Language.- Visual Representation.- Visualization for Information Retrieval.- Visualization Pipeline.- Visualizing Categorical Data.- Visualizing Clustering Results.- Visualizing Hierarchical Data.- Visualizing Network Data.- Visualizing Quantitative Data.- Volume.- Voronoi Diagrams.- W3C.- WAN Data Replication.- Wavelets on Streams.- Weak Consistency Models for Replicated Data.- Weak Equivalence.- Web 2.0/3.0.- Web Advertising.- Web Characteristics and Evolution.- Web Crawler Architecture.- Web Data Extraction System.- Web ETL.- Web Harvesting.- Web Information Extraction.- WEB Information Retrieval Models.- Web Mashups.- Web Page Quality Metrics.- Web Question Answering.- Web Search Query Rewriting.- Web Search Relevance Feedback.- Web Search Relevance Ranking.- Web Search Result Caching and Prefetching.- Web Search Result De-duplication and Clustering.- Web Services.- Web Services and the Semantic Web for Life Science Data.- Web Spam Detection.- Web Transactions.- Web Views.- What-If Analysis.- WIMP Interfaces.- Window operator in RDBMS.- Window-based Query Processing.- Windows.- Workflow Constructs.- Workflow Evolution.- Workflow Join.- Workflow Management.- Workflow Management and Workflow Management System.- Workflow Management Coalition.- Workflow Model.- Workflow Model Analysis.- Workflow Patterns.- Workflow Schema.- Workflow Transactions.- Wrapper Induction.- Wrapper Maintenance.- Wrapper Stability.- Write Once Read Many.- XML.- XML Access Control.- XML Attribute.- XML Benchmarks.- XML Compression.- XML Document.- XML Element.- XML Indexing.- XML Information Integration.- XML Integrity Constraints.- XML Metadata Interchange.- XML Metadata Interchange Specification (XMI).- XML Parsing, SAX/DOM.- XML Process Definition Language.- XML Programming.- XML Publish/Subscribe.- XML Publishing.- XML Retrieval.- XML Schema.- XML Selectivity Estimation.- XML Storage.- XML Stream Processing.- XML Tree Pattern, XML Twig Query.- XML Tuple Algebra.- XML Typechecking.- XML Types.- XML Updates.- XML Views.- XPath/XQuery.- XQuery Full-Text.- XQuery Processors.- XSL/XSLT.- Zero-One Laws.- Zooming Techniques.- α-nDCG.-

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Book SynopsisImplement the Snowflake Data Cloud using best practices and reap the benefits of scalability and low-cost from the industry-leading, cloud-based, data warehousing platform. This book provides a detailed how-to explanation, and assumes familiarity with Snowflake core concepts and principles. It is a project-oriented book with a hands-on approach to designing, developing, and implementing your Data Cloud with security at the center. As you work through the examples, you will develop the skill, knowledge, and expertise to expand your capability by incorporating additional Snowflake features, tools, and techniques. Your Snowflake Data Cloud will be fit for purpose, extensible, and at the forefront of both Direct Share, Data Exchange, and Snowflake Marketplace. Building the Snowflake Data Cloud helps you transform your organization into monetizing the value locked up within your data. As the digital economy takes hold, with data volume, velociTable of Contents Part I. Context 1. The Snowflake Data Cloud 2. Breaking Data Siloes Part II. Concepts 3. Architecture 4. Account Security5. Role Based Access Control (RBAC)6. Account Usage StorePart III. Tools7. Ingesting Data8. Data Pipelines9. Data Presentation10. Semi Structured and Unstructured DataPart IV. Management11. Query Optimizer Basics12. Data Management13. Data Modelling14. Snowflake Data Cloud By Example

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Book SynopsisThis book constitutes the proceedings of the 7th International Conference on Business Intelligence, CBI 2022, which took place in Khouribga, Morocco, during May 26-28, 2022. The 23 full papers included in this book were carefully reviewed and selected from a total of 68 submissions. They were organized in topical sections as follows: decision support and artificial intelligence; business intelligence and database; and optimization and dynamic programming.Table of ContentsDecision Support and Artificial Intelligence.- Optimization Focused On Parallel Fuzzy Deep Belief Neural Network For Opinion Mining.- A Convolutional Neural Networks-Based Approach For Potato Disease Classification.- Performance Investigation of a Proposed CBIR Search Engine Using Deep Convolu-tional Neural Networks.- Decision Boundary to improve the sensitivity of deep neural networks models. - Facial Expression Recognition Using a Hybrid ViT-CNN Aggregator.- Machine Learning Approach to Automate Decision Support on Information System Attacks.- Deep Reinforcement Learning for Bitcoin Trading.- An exploration of student grade retention prediction using machine learning algorithms.- Deep Learning Model For Educational Recommender Systems.- Comparative Study of Deep Learning Models for detection and classification of intracranial hemorrhage.- Business Intelligence and Database.- Increasing Student Engagement in Lessons and Assessing MOOC Participants Through Artificial Intelligence. -Mining frequents itemset and association rules in diabetic dataset.- Automatic text summarization for Moroccan Arabic dialect using an artificial intelligence approach.- Automatic Change Detection based on the Independent Component Analysis and Fuzzy C-means Methods.- Sentiment analysis decision system for tracking climate change opinion in Twitter.- Analysis of Decision Tree Algorithms for Diabetes Prediction.- How far can Deep Learning improve Arabic Part of Speech Tagging.- Optimization and Dynamic programming.- Analysis of Several Algorithms for DOA Estimation in Two Different Communication Models by a Comparative Study.- A Novel hybrid Approach for improving the accuracy of the Supervised Link Prediction based on Graph Structure Features in Social Networks. - Intelligent system based on GAN model for decision support in brain Tumor segmentation.- Hospital room management for Covid-19 patients using Petri nets.- Dimensionality reduction of MI-EEG data via convolutional autoencoders with a low size dataset.- Car tracking technique for DLES Project.

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Book SynopsisThis book constitutes the refereed proceedings of the 15th IAPR International Workshop on Document Analysis Systems, DAS 2022, held in La Rochelle, France, in May 2022.The full papers presented were carefully reviewed and selected from numerous submissions addressing key techniques of document analysis.

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Book SynopsisThis volume constitutes the papers of several workshops which were held in conjunction with the 27th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held as virtual event in April 2022. The 30 revised full papers presented in this book were carefully reviewed and selected from 65 submissions. DASFAA 2022 presents the following five workshops: · First workshop on Pattern mining and Machine learning in Big complex Databases (PMBD 2021) · 6th International Workshop on Graph Data Management and Analysis (GDMA 2022) · First International Workshop on Blockchain Technologies (IWBT2022) · 8th International Workshop on Big Data Management and Service (BDMS 2022) · First workshop on Managing Air Quality Through Data Science · 7th International Workshop on Big Data Quality Management (BDQM 2022). Table of ContentsAn Algorithm for Mining Fixed-Length High Utility Itemsets.- A Novel Method to Create Synthetic Samples with Autoencoder Multi-layer Extreme Learning Machine.- Pattern Mining: Current Challenges and Opportunities.- Why not to Trust Big Data: Identifying Existence of Simpson’s Paradox Localized Metric Learning for Large Multi-Class Extremely Imbalanced Face Database.- Top-k dominating queries on incremental datasets.- Collaborative Blockchain based Distributed Denial of Service Attack Mitigation approach with IP Reputation System.- Model-Driven Development of Distributed Ledger Applications Towards a Blockchain Solution for Customs Duty-Related Fraud.- Securing Cookies/Sessions through Non-Fungible Tokens.- Chinese Spelling Error Detection and Correction Based on Knowledge Graph Construction and Application of Event Logic Graph: A Survey.- Enhancing Low-resource Languages Question Answering with Syntactic Graph.- Profile Consistency Discrimination.- H-V：An Improved Coding Layout based on Erasure Coded Storage System.- Astral: An Autoencoder-based Model for Pedestrian Trajectory Prediction of Variable-Length.- A Survey on Spatiotemporal Data Processing Techniques in Smart Urban Rail.- Fast Vehicle Track Counting in Traffic Video.- Summary A Traffic Summarization System using Semantic Words.- Attention_Cooperated_Reinforcement_Learning_for_Multi_agent_Path_Planning.- Big Data-driven Stable Task Allocation in Ride-hailing Services.- Weighted_Mean_Field_Multi_Agent_Reinforcement_Learning_via_Reward_Attribution_Decomposition.- Evaluating Presto and SparkSQL with TPC-DS.- Optimizing the Age of Sensed Information in Cyber-Physical Systems.- Aggregate Query Result Correctness using pattern Tables.- Time Series Data Quality Enhancing based on pattern Alignment.- Research on Feature extraction method of data quality intelligent detection.- Big Data Resources to Support Research Opportunities on Air Pollution Analysis in India.- Air Quality Data Collection in Hyderabad Using Low-cost Sensors: Initial Experiences.- Visualizing Spatio-Temporal Variation of Ambient Air Pollution in Four Small Towns in India.

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Book SynopsisThis book constitutes the refereed proceedings of the 12th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2022, held in Helsinki, Finland, in June 2022. The 13 full papers presented were carefully reviewed and selected from 21 submissions. The papers address various topics such as information and knowledge systems, including submissions that apply ideas, theories or methods from specific disciplines to information and knowledge systems. Examples of such disciplines are discrete mathematics, logic and algebra, model theory, databases, information theory, complexity theory, algorithmics and computation, statistics and optimization.Table of ContentsOn Sampling Representatives of Relational Schemas with a Functional Dependency.- On the expressive power of message-passing neural networks as global feature map transformers.- Assumption-Based Argumentation for Extended Disjunctive Logic Programming.- A graph based semantics for Logical Functional Diagrams in power plant controllers.- Database Repair via Event-Condition-Action Rules in Dynamic Logic.- Statistics of RDF store for querying knowledge graphs.- Can you answer while you wait?.- The implication problem for functional dependencies and variants of marginal distribution equivalences.- Approximate Keys and Functional Dependencies in Incomplete Databases With Limited domains.- The Fault-Tolerant Cluster-Sending Problem.- Optimizing multiset relational algebra queries using weak-equivalent rewrite rules.- Properties of System W and its Relationships to Other Inductive Inference Operators.- Towards the Evaluation of Action Reversibility in STRIPS using Domain Generators.

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Book SynopsisThe volume LNAI 13546 constitutes the refereed proceedings of the 23rd Annual Conference Towards Autonomous Robotic Systems, TAROS 2022, held in Culham, UK, in September 2022. The 14 full papers and 10 short papers were carefully reviewed and selected from 38 submissions. Organized in the topical sections "Algorithms" and "Systems", they discuss significant findings and advances in the following areas: Robotic Grippers and Manipulation; Soft Robotics, Sensing and Mobile Robots; Robotic Learning, Mapping and Planning; Robotic Systems and Applications.Table of ContentsA distributed approach to haptic simulation.- A Novel Two-Hand-Inspired Hybrid Robotic End-Effector Fabricated Using 3D Printing.- Investigating the relationship between posture and safety in teleoperational tasks: A pilot study in improved operational safety through enhanced human-machine interaction.- Design and Analysis of an End Effector Using the Fin Ray Structure for Integrated Limb Mechanisms.- Trigger-Assisted Ambidextrous Control Framework for Teleoperation of Two Legged Manipulators.- Teleoperating a Legged Manipulator through Whole-Body Control.- In-silico Design and Computational Modelling of Electroactive Polymer based Soft Robotics.- Exploration of Underwater Storage Facilities with Swarm of Micro-Surface Robots.- Characterization of an Inflatable Soft Actuator and Tissue Interaction for In Vitro Mechanical Stimulation of Tissue.- EMap: Real-time terrain estimation.- Design and Preliminary In-Classroom Evaluation\\of a Low-Cost Educational Mobile Robot.- Internal State-based Risk Assessment for Robots in Hazardous Environment.- Investigating Scene Visibility Estimation within ORB-SLAM3.- Tactile and Proprioceptive Online Learning in Robotic Contour Following.- Learning cooperative behaviours in adversarial multi-agent systems.- Task Independent Safety Assessment for Reinforcement Learning.- Sensing Anomalies as Potential Hazards: Datasets and Benchmarks.- Integration and robustness analysis of the Buzz swarm programming language with the Pi-puck robot platform.- Implementing and assessing a remote teleoperation setup with a Digital Twin using cloud networking.- Agent-Based Simulation of Multi-Robot Soil Compaction Mapping.- A-EMS: An Adaptive Emergency Management System for Autonomous Agents in Unforeseen Situations.- Towards Scalable Multi-Robot Systems by Partitioning the Task Domain.- Effectiveness of brush operational parameters for robotic debris removal.- Automatic, Vision-Based Tool Changing Solution for Dexterous Teleoperation Robots in a Nuclear Glovebox

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Book SynopsisDieses Buch bietet einen Überblick über Data-Mining-Methoden, die durch Software veranschaulicht werden. Beim Wissensmanagement geht es um die Anwendung von menschlichem Wissen (Erkenntnistheorie) mit den technologischen Fortschritten unserer heutigen Gesellschaft (Computersysteme) und Big Data, sowohl bei der Datenerfassung als auch bei der Datenanalyse. Es gibt drei Arten von Analyseinstrumenten. Die deskriptive Analyse konzentriert sich auf Berichte über das, was passiert ist. Bei der prädiktiven Analyse werden statistische und/oder künstliche Intelligenz eingesetzt, um Vorhersagen treffen zu können. Dazu gehört auch die Modellierung von Klassifizierungen. Die diagnostische Analytik kann die Analyse von Sensoreingaben anwenden, um Kontrollsysteme automatisch zu steuern. Die präskriptive Analytik wendet quantitative Modelle an, um Systeme zu optimieren oder zumindest verbesserte Systeme zu identifizieren. Data Mining umfasst deskriptive und prädiktive Modellierung. Operations Research umfasst alle drei Bereiche. Dieses Buch konzentriert sich auf die deskriptive Analytik.Das Buch versucht, einfache Erklärungen und Demonstrationen einiger deskriptiver Werkzeuge zu liefern. Es bietet Beispiele für die Auswirkungen von Big Data und erweitert die Abdeckung von Assoziationsregeln und Clusteranalysen. Kapitel 1 gibt einen Überblick im Kontext des Wissensmanagements. Kapitel 2 erörtert einige grundlegende Softwareunterstützung für die Datenvisualisierung. Kapitel 3 befasst sich mit den Grundlagen der Warenkorbanalyse, und Kapitel 4 demonstriert die RFM-Modellierung, ein grundlegendes Marketing-Data-Mining-Tool. Kapitel 5 demonstriert das Assoziationsregel-Mining. Kapitel 6 befasst sich eingehender mit der Clusteranalyse. Kapitel 7 befasst sich mit der Link-Analyse. Die Modelle werden anhand geschäftsbezogener Daten demonstriert. Der Stil des Buches ist beschreibend und versucht zu erklären, wie die Methoden funktionieren, mit einigen Zitaten, aber ohne tiefgehende wissenschaftliche Referenzen. Die Datensätze und die Software wurden so ausgewählt, dass sie für jeden Leser, der über einen Computeranschluss verfügt, weithin verfügbar und zugänglich sind.Table of Contents

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Book SynopsisThis book constitutes the refereed proceedings of the 25th International Symposium on Formal Methods, FM 2023, which took place in Lübeck, Germany, in March 2023. The 26 full paper, 2 short papers included in this book were carefully reviewed and selected rom 95 submissions. They have been organized in topical sections as follows: SAT/SMT; Verification; Quantitative Verification; Concurrency and Memory Models; Formal Methods in AI; Safety and Reliability. The proceedings also contain 3 keynote talks and 7 papers from the industry day. Table of Contents​Keynotes.- Symbolic Computation in Automated Program Reasoning.- The next big thing: from embedded systems to embodied actors.- Intelligent and Dependable Decision-Making Under Uncertainty.- A Coq formalization of Lebesgue Induction Principle and Tonelli’s Theorem.- SAT/SMT.- Railway Scheduling Using Boolean Satisfiability Modulo Simulations.- SMT Sampling via Model-Guided Approximation.- Efficient SMT-based Network Fault Tolerance Verification.- Verification I.- Formalising the Prevention of Microarchitectural Timing Channels by Operating Systems.- Can we Communicate? Using Dynamic Logic to Verify Team Automata.- The ScalaFix equation solver.- HHLPy: Practical Verification of Hybrid Systems using Hoare Logic.- Quantitative Verification.- symQV: Automated Symbolic Verification of Quantum Programs.- PFL: a Probabilistic Logic for Fault Trees.- Energy Buechi Problems.- QMaude: quantitative specification and verification in rewriting logic.- Concurrency and Memory Models.- Minimisation of Spatial Models using Branching Bisimilarity.- Reasoning about Promises in Weak Memory Models with Event Structures.- A fine-grained semantics for arrays and pointers under weak memory models.- VeyMont: Parallelising Verified Programs instead of Verifying Parallel Programs.- Verification 2.- Verifying At the Level of Java Bytecode.- Abstract Alloy Instances.- Monitoring the Internet Computer.- Word Equations in Synergy with Regular Constraints.- Formal Methods in AI.- Verifying Feedforward Neural Networks for Classification in Isabelle/HOL.- SMPT: A Testbed for Reachabilty Methods in Generalized Petri Nets.- The Octatope Abstract Domain for Verification of Neural Networks.- Program Semantics and Verification Technique for AI-centred Programs.- Safety and Reliability.- Tableaux for Realizability of Safety Specifications.- A Decision Diagram Operation for Reachability.- Formal Modelling of Safety Architecture for Responsibility-AwareAutonomous Vehicle via Event-B Refinement.- A Runtime Environment for Contract Automata.- Industry Day.- Formal and Executable Semantics of the Ethereum Virtual Machine in Dafny.- Shifting Left for Early Detection of Machine-Learning Bugs.- A Systematic Approach to Automotive Security.- Specification-Guided Critical Scenario Identification for Automated Driving.- Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks.- Backdoor Mitigation in Deep Neural Networks via Strategic Retraining.- veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System.

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Book SynopsisThis book constitutes the refereed proceedings of the 8th International Symposium, UNet 2022, held in Montreal, QC, Canada, during October 25–27, 2022. The 17 full papers included in this book were carefully reviewed and selected from 43 submissions. Moreover, 4 additional invited papers have been also considered. They were organized in topical sections as follows: ​Spectrum Management and Channel Prediction, Resource Allocation in 5G/6G, Internet of Things and Vehicular Communications, Artificial Intelligence-Driven Communications, Pervasive Services and Cyber Security.Table of ContentsSpectrum Management and Channel Prediction.- On the Influence of Microscopic Mobility in Modelling Pedestrian Communication.- Low Profile CPW Fed Tri-Band Millimeter Wave Antenna Design for Future 5G Application.- Trading off Controlled System Energy and Wireless Communication Energy.- Statistical Moments of the Temporal Spectrum of Electromagnetic Waves in the Equatorial Ionosphere.- Resource Allocation in 5G/6G.- Towards Facilitating URLLC in UAV-Enabled MEC Systems for 6G Networks.- Resource Allocation and Power Control for Heterogeneous Cellular Network and D2D Communications.- Optimized Network Coding With Real-Time Loss Prediction for Hybrid 5G Networks.- TCP-RTA: Real-Time Topology Adaptiveness for Congestion Control in TCP.- Rio_DSA: Redirecting I/O Scheme for Dynamic Storage Allocation on Docker Container.- Internet of Things and Vehicular Communications.- VANET-Based Traffic Light Management for an Emergency Vehicle.- Deep Reinforcement Learning to Improve Vehicle-to-Vulnerable Road User Communications in C-V2X.- Pervasive Computing for Efficient Intra-UAV Connectivity: Based on Context-Awareness.- Road Accident Analysis of Dhaka City Using Counter Propagation Network.- Artificial Intelligence-Driven Communications.- Reinforcement Learning for Protocol Synthesis in Resource-Constrained Wireless Sensor and IoT Networks.- Distributional Reinforcement Learning for VoLTE Closed Loop Power Control in Indoor Small Cells.- Reinforcement Learning Aided Routing in Tactical Wireless Sensor Networks.- A Green and Scalable Clustering for Massive IoT Sensors with Selective Deactivation.- Pervasive Services and Cyber Security.- Threat Mitigation Model With Low False Alarm Rate Based on Hybrid Deep Belief Network.- On Feature Selection Algorithms for Effective Botnet Detection.- A Novel Hybrid Deep Learning Model for Crop Disease Detection Using BEGAN.- Multivariate Skewness and Kurtosis for Detecting Wormhole Attack in VANETs.

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Book SynopsisThis book constitutes the refereed post-conference proceedings the 14th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2022, which was held in Sydney, NSW, Australia, on September 5, 2022.The 5 revised full papers presented were carefully selected from 12 submissions. The conference focuses on Pick and Mix Isolation Levels; Benchmarking considerations for Trustworthy and Responsible AI (Panel); Preliminary Scaling Characterization with TPCx-AI and New Initiatives. Table of ContentsPick and Mix Isolation Levels: Mixed Serialization Graph Testing.- BODS: A Benchmark on Data Sortedness.- Disaggregated Database Management Systems (Panel).- TPCx-AI on NVIDIA Jetson.- More the Merrier: Comparative evaluation of TPCx-AI and MLPerf Benchmarks for AI.- Preliminary Scaling Characterization with TPCx-AI.- 4mbench: Performance Benchmark of Manufacturing Business Database.- Benchmarking considerations for Trustworthy and Responsible AI (Panel).- TPCx-AI: First Adopter's Experience Report.- New Initiatives in the TPC.

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Book SynopsisThis book constitutes the joint refereed proceedings of the 22nd International Conference on Internet of Things, Smart Spaces, and Next Generation Networks and Systems, NEW2AN 2022, held in Tashkent, Uzbekistan, in December 2022.The 58 regular papers presented in this volume were carefully reviewed and selected from 282 submissions. The papers of NEW2AN address various aspects of next-generation data networks, while special attention is given to advanced wireless networking and applications. In particular, the authors have demonstrated novel and innovative approaches to performance and efficiency analysis of 5G and beyond systems, employed game-theoretical formulations, advanced queuing theory, and machine learning. It is also worth mentioning the rich coverage of the Internet of Things, optics, signal processing, as well as digital economy and business aspects.Table of ContentsTangential shear stress in an oscillatory flow of a viscoelastic fluid in a flat channel.- Comparison of Finite Difference Schemes of Different Orders of Accuracy for the Burgers Wave Equation Problem.- Numerical solution of the combustion process using the computer package ANSYS fluent.- Simulation Modeling of Reliability of Packet Switching Unit.- Analytical Model for Assessing the Reliability of the Functioning of the Adaptive Switching Node.- Artificial intelligence software architecture in the field of cardiology and application in the cardio vessel project using CJM and customer development methods.- Using discretization and numerical methods of problem 1d-3d-1d model for blood vessel walls with Navier-Stokes.- Numerical simulation of a flow in a two-dimensional channel on the basis of a two-liquid turbulence model.- Application fuzzy neural network methods to detect cryptoattacks on financial information systems based on blockchain technology.- Method authentication of objects information communication systems.- TEDCTSSA: Trust Enabled Data Collection Technique based Sparrow Search Algorithm for WSN-based Applications.- ISTOA: An improved Sooty Tern Optimization Algorithm for multilevel threshold image segmentation.- Implementing digital transformation in the logistics system of Uzbekistan.- Numerical modeling of vertical axis wind turbines using ANSYS FLUENT software.- "i’ll wait 4 ur answr!” A Study on Modern Style of Cyber-Writing and User Reactions.- Improvement of information support in intelligent information energy systems.- The Assessment of the Effectiveness of the Development of Digital Technologies in Commercial Banks in Uzbekistan.- The Study of the Impact of the Digital Economy on the Growth of E-Government Services in Uzbekistan.- Deep learning algorithm for classifying dilated cardiomyopathy and hypertrophy cardiomyopathy in transport workers.- eCommerce benchmarking: theoretical background, variety of types, and application of competitive-integration benchmarking.- Cryptocurrencies as the money of the future.- A Data Security Technique Combining Asymmetric Cryptography and Compressive Sensing for IoT Enabled Wireless Sensor Networks.- Energy Efficient and Secure Scheme based Compressive Sensing method for Internet of Vehicles.- Impact of digital technologies on women’s employment.- The impact of digitalisation on the safe development of individuals in society.- Econometric Evaluation of the Efficiency of the Management of theEnterprise through the Supply of Raw Materials in Oil Enterprises in the Conditions of the Digital Economy.- The impact of digital infrastructure, foreign direct investment and trade openness on economic growth: In the case of Uzbekistan.- The impact of the financial ratios on the financial performance. A caseof Chevron Corporation (CVX).- The impact of the digitalisation of payment systems on the profitabilityof commercial banks.- The main aspects and benefits of digital transformation of business entities.- The influence of the capital structure of state enterprises on the profitability of the enterprise.- Exploring the development of China’s digital trade in the context of the domestic and international double cycle.- A systematic mapping study of using the cutting-edge technologies in marketing: the state of the art of four key new-age technologies.- Social Media Marketing for Educational Purposes: Goals, Objectivesand Content of the Training Course.- Digital Marketing and Smart Technology Marketing Systems as thefuture of metaverse.- The impact of the digital economy on the development of higher education.- What is the state-of-the-art contribution of the higher education system to the digital economy: a systematic mapping study on changes and challenges.- Innovating primary education of promoting students’ languagecompetencies through mobile assisted language learning approach: Selection framework of innovative digital technologies.- Econometric assessment of the dynamics of development of the export authority of small business and private business subjects in the conditions of the digital economy.- The significance of the Internet of Things for ensuring the smooth operation of network functions in fintech.- Impact of E-government on Poverty Rate: a Cross- Country Empirical Assessment.- An empirical investigation of the relationship between e-government development and multidimensional poverty.- On Digital Twin Software and Cyber Threats.- On local services based on non-standard Wi-Fi Direct usage model.- Compatibility analysis between 5G NR and ultra-wideband devices in the 6425-7125 MHz frequency band.- 6 GHz band sharing study for FWA base stations and GEO satellite receivers.- Federated Learning Strategies Over Wireless Channels.- Data Routing in UAV Networks with Multiple Data Sources using Steiner Tree.- Reduced complexity distributed arithmetic architecture for FIR filters.- Blockchain-driven Hybrid Model for IoT Authentication.- An Heuristic Approach for Mapping of Service Function Chains in Softwarized 5G Networks.- Multi-threshold hysteresis-Based Congestion Control for UAV-based Detection Sensor Network.- Analysis of the capacity gain of Probability Shaping QAM.- LoRa Mesh Network for Image Transmission: An Experimental Study.- Blockchain Technology – Innovation for Better Collaboration and Increased Efficieny. The U.S. Logistics and Trucking Industry Case.- Econometric Study of the Impact of the Digital Economy on the Gross Product in Anti-monopoly Conditions.- Predictive models for effective management of e- commerce in New Uzbekistan.- The role of IT on transportation, logistics and the economic growth among Central Asian countries.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the 6th IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2023, held in Denton, TX, USA, in November 2023.The 36 full papers and 27 short papers presented were carefully reviewed and selected from 84 submissions. The papers offer insights into the latest innovations, challenges, and opportunities in IoT, covering a wide array of topics, including IoT architectures, security and privacy, data analytics, edge computing, and applications in various domains.Table of ContentsArtificial Intelligence and Machine Learning Technologies for IoT (AMT).- Energy-Aware Security for IoT (EAS).- Edge AI for Smart Wearables (EAW).- Hardware/Software Solutions for IoT and CPS (HSS).- AI and Big Data for Next-G Internet of Medical Things (IoMT).- IoT for Wearables and Smart Devices (IWS).- Metaverse for IoT (MIoT).- Technologies for Smart Agriculture (TSA).- Student Research Forum (SRF).

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Book SynopsisTable of ContentsInstallation und Start von WordPerfect.- Abbildung (Grafik).

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