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Author: John Mylopoulos
Publisher: Morgan Kaufmann
ISBN: 0080886620
Category : Computers
Languages : en
Pages : 688
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Book Description
The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.
Author: John Mylopoulos
Publisher: Morgan Kaufmann
ISBN: 0080886620
Category : Computers
Languages : en
Pages : 688
Get Book
Book Description
The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.
Author: Bonnie Lynn Webber
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 566
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Book Description
The purpose of this collection is to make accessible in one place a number of the seminal research papers in the field of aritificial intelliigence. These papers cover a wide variety of topics; some are theoretical and some experimental. As many of the papers included here are difficult to find elsewhere, having originally been published in conference proceedings or journals that are no longer in print, the researcher or student will find this volume a valuable sourcebookof fundamental AI research. The editors have added useful introductions to each section and a comprehensive subject index.
Author: Alan H. Bond
Publisher: Morgan Kaufmann
ISBN: 1483214443
Category : Computers
Languages : en
Pages : 668
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Book Description
Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. "Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided.
Author: Michael L. Brodie
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 698
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Book Description
This book will be an invaluable source of ideas and a current and future framework for both AI and database research scientists and professionals.
Author: S. Kanimozhi Suguna
Publisher: CRC Press
ISBN: 1000375528
Category : Computers
Languages : en
Pages : 331
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Book Description
Addresses the complete functional framework workflow in Artificial Intelligence technology Explores basic and high-level concepts Based on the latest technologies covering the major challenges, issues, and advances in AI Discusses intelligent and automated system through AI and its implications to the real-world Presents data acquisition and case studies related to data-intensive technologies
Author: Joost Nico Kok
Publisher: EOLSS Publications
ISBN: 184826125X
Category : Artificial intelligence
Languages : en
Pages : 418
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Book Description
Artificial Intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty Encyclopedias. The Theme on Artificial Intelligence provides the essential aspects and fundamentals of Artificial Intelligence: Definition, Trends, Techniques, and Cases; Logic in Artificial Intelligence (AI); Computational Intelligence; Knowledge Based System Development Tools. It is aimed at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers.
Author: Neeraj Mohan
Publisher: CRC Press
ISBN: 1000460541
Category : Technology & Engineering
Languages : en
Pages : 297
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Book Description
This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.
Author: M.L. Brodie
Publisher: Springer Science & Business Media
ISBN: 1461251966
Category : Computers
Languages : en
Pages : 508
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Book Description
The growing demand for systems of ever-increasing complexity and precision has stimulated the need for higher level concepts, tools, and techniques in every area of Computer Science. Some of these areas, in particular Artificial Intelligence, Databases, and Programming Lan guages, are attempting to meet this demand by defining a new, more abstract level of system description. We call this new level conceptual in recognition of its basic conceptual nature. In Artificial Intelligence, the problem of designing an expert system is seen primarily as a problem of building a knowledge base that repre sents knowledge about an enterprise. Consequently, Knowledge Repre sentation is viewed as a central issue in Artificial Intelligence research. Database design methodologies developed during the last five years are almost unanimous in offering semantic data models in terms of which the designer directly and naturally models an enterprise before proceed ing to a detailed logical and physical database design. In Programming Languages, different forms of abstraction which allow implementation independent specifications of data, functions, and control have been a major research theme for a decade. To emphasize the common goals of these three research efforts, we call this new activity conceptual modelling.
Author: K. Gayathri Devi
Publisher: CRC Press
ISBN: 1000179516
Category : Computers
Languages : en
Pages : 250
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Book Description
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning
Author: Maciej Huk
Publisher: Springer
ISBN: 3030141322
Category : Technology & Engineering
Languages : en
Pages : 438
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Book Description
This book presents research reports selected to indicate the state of the art in intelligent and database systems and to promote new research in this field. It includes 34 chapters based on original research presented as posters at the 11th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2019), held in Yogyakarta, Indonesia on 8–11 April 2019. The increasing use of intelligent and database systems in various fields, such as industry, medicine and science places those two elements of computer science among the most important directions of research and application, which currently focuses on such key technologies as machine learning, cloud computing and processing of big data. It is estimated that further development of intelligent systems and the ability to gather, store and process enormous amounts of data will be needed to solve a number of crucial practical and theoretical problems. The book is divided into five parts: (a) Sensor Clouds and Internet of Things, (b) Machine Learning and Decision Support Systems, (c) Computer Vision Techniques and Applications, (d) Intelligent Systems in Biomedicine, and (e) Applications of Intelligent Information Systems. It is a valuable resource for researchers and practitioners interested in increasing the synergy between artificial intelligence and database technologies, as well as for graduate and Ph.D. students in computer science and related fields.
