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Knowledge Integration Methods for Probabilistic Knowledge-based Systems

Author: Van Tham Nguyen

Publisher: CRC Press

Published: 2022-12-30

Total Pages: 176

ISBN-13: 1000809994

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Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years. Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more. This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.

Book Synopsis Knowledge Integration Methods for Probabilistic Knowledge-based Systems by : Van Tham Nguyen

Download or read book Knowledge Integration Methods for Probabilistic Knowledge-based Systems written by Van Tham Nguyen and published by CRC Press. This book was released on 2022-12-30 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years. Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more. This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.

Probabilistic Graphical Models

Author: Linda C. van der Gaag

Publisher: Springer

Published: 2014-09-11

Total Pages: 609

ISBN-13: 3319114336

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This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.

Book Synopsis Probabilistic Graphical Models by : Linda C. van der Gaag

Download or read book Probabilistic Graphical Models written by Linda C. van der Gaag and published by Springer. This book was released on 2014-09-11 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.

Computational Collective Intelligence

Author: Ngoc Thanh Nguyen

Publisher: Springer

Published: 2018-08-27

Total Pages: 578

ISBN-13: 3319984438

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This two-volume set (LNAI 11055 and LNAI 11056) constitutes the refereed proceedings of the 10th International Conference on Collective Intelligence, ICCCI 2018, held in Bristol, UK, in September 2018 The 98 full papers presented were carefully reviewed and selected from 240 submissions. The conference focuses on knowledge engineering and semantic web, social network analysis, recommendation methods and recommender systems, agents and multi-agent systems, text processing and information retrieval, data mining methods and applications, decision support and control systems, sensor networks and internet of things, as well as computer vision techniques.

Book Synopsis Computational Collective Intelligence by : Ngoc Thanh Nguyen

Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2018-08-27 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (LNAI 11055 and LNAI 11056) constitutes the refereed proceedings of the 10th International Conference on Collective Intelligence, ICCCI 2018, held in Bristol, UK, in September 2018 The 98 full papers presented were carefully reviewed and selected from 240 submissions. The conference focuses on knowledge engineering and semantic web, social network analysis, recommendation methods and recommender systems, agents and multi-agent systems, text processing and information retrieval, data mining methods and applications, decision support and control systems, sensor networks and internet of things, as well as computer vision techniques.

Utilizing Data and Knowledge Mining for Probabilistic Knowledge Bases

Author: Daniel Joseph Stein

Publisher:

Published: 1996-12-01

Total Pages: 68

ISBN-13:

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Problems can arise whenever inferencing is attempted on a knowledge base that is incomplete. Our work shows that data mining techniques can be applied to fill in incomplete areas in Bayesian Knowledge Bases (BKBs), as well as in other knowledge-based systems utilizing probabilistic representations. The problem of inconsistency in BKBs has been addressed in previous work, where reinforcement learning techniques from neural networks were applied. However, the issue of automatically solving incompleteness in BKBs has yet to be addressed. Presently, incompleteness in BKBs is repaired through the application of traditional knowledge acquisition techniques. We show how association rules can be extracted from databases in order to replace excluded information and express missing relationships. A methodology for incorporating those results while maintaining a consistent knowledge base is also included.

Book Synopsis Utilizing Data and Knowledge Mining for Probabilistic Knowledge Bases by : Daniel Joseph Stein

Download or read book Utilizing Data and Knowledge Mining for Probabilistic Knowledge Bases written by Daniel Joseph Stein and published by . This book was released on 1996-12-01 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Problems can arise whenever inferencing is attempted on a knowledge base that is incomplete. Our work shows that data mining techniques can be applied to fill in incomplete areas in Bayesian Knowledge Bases (BKBs), as well as in other knowledge-based systems utilizing probabilistic representations. The problem of inconsistency in BKBs has been addressed in previous work, where reinforcement learning techniques from neural networks were applied. However, the issue of automatically solving incompleteness in BKBs has yet to be addressed. Presently, incompleteness in BKBs is repaired through the application of traditional knowledge acquisition techniques. We show how association rules can be extracted from databases in order to replace excluded information and express missing relationships. A methodology for incorporating those results while maintaining a consistent knowledge base is also included.

Uncertain Information Processing In Expert Systems

Author: Petr Hajek

Publisher: CRC Press

Published: 1992-06-29

Total Pages: 310

ISBN-13: 9780849363689

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Uncertain Information Processing in Expert Systems systematically and critically examines probabilistic and rule-based (compositional, MYCIN-like) systems, the two most important families of expert systems dealing with uncertainty. The book features a detailed introduction to probabilistic systems (including methods using graphical models and methods of knowledge integration), an analysis of compositional systems based on algebraic considerations, an application of graphical models, and the Dempster-Shafer theory of evidence and its use in expert systems. The book will be useful to anyone working in artificial intelligence, statistical computing, symbolic logic, and expert systems.

Book Synopsis Uncertain Information Processing In Expert Systems by : Petr Hajek

Download or read book Uncertain Information Processing In Expert Systems written by Petr Hajek and published by CRC Press. This book was released on 1992-06-29 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertain Information Processing in Expert Systems systematically and critically examines probabilistic and rule-based (compositional, MYCIN-like) systems, the two most important families of expert systems dealing with uncertainty. The book features a detailed introduction to probabilistic systems (including methods using graphical models and methods of knowledge integration), an analysis of compositional systems based on algebraic considerations, an application of graphical models, and the Dempster-Shafer theory of evidence and its use in expert systems. The book will be useful to anyone working in artificial intelligence, statistical computing, symbolic logic, and expert systems.

A Methodology for Uncertainty in Knowledge-Based Systems

Author: Kurt Weichselberger

Publisher:

Published: 2014-01-15

Total Pages: 320

ISBN-13: 9783662170854

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Book Synopsis A Methodology for Uncertainty in Knowledge-Based Systems by : Kurt Weichselberger

Download or read book A Methodology for Uncertainty in Knowledge-Based Systems written by Kurt Weichselberger and published by . This book was released on 2014-01-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Uncertainty Models for Knowledge-based Systems

Author: Irwin R. Goodman

Publisher: North Holland

Published: 1985

Total Pages: 674

ISBN-13:

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Book Synopsis Uncertainty Models for Knowledge-based Systems by : Irwin R. Goodman

Download or read book Uncertainty Models for Knowledge-based Systems written by Irwin R. Goodman and published by North Holland. This book was released on 1985 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence Abstracts

Author:

Publisher:

Published: 1991

Total Pages: 448

ISBN-13:

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Book Synopsis Artificial Intelligence Abstracts by :

Download or read book Artificial Intelligence Abstracts written by and published by . This book was released on 1991 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Advanced Topics in Artificial Intelligence

Author: Vladimír Mařík

Publisher: Springer

Published: 1992

Total Pages: 504

ISBN-13:

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"This volume contains the texts of 26 lectures and contributions to the program of the International Summer School on Advanced Topics in Artificial Intelligence held in Prague, Czechoslovakia, July 6-17, 1992. The summerschool was intended for (postgraduate) students, researchers and all those who want to learn about recent progress in both theoretical and applied AI. The papers in the volume are organized into nine parts: - Introduction - Logic and logic programming - Machine learning - Planning and scheduling - Uncertainty - Second generation expert systemsand knowledge engineering - Qualitative reasoning - Neurocomputing -Natural language and interfaces"--PUBLISHER'S WEBSITE.

Book Synopsis Advanced Topics in Artificial Intelligence by : Vladimír Mařík

Download or read book Advanced Topics in Artificial Intelligence written by Vladimír Mařík and published by Springer. This book was released on 1992 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This volume contains the texts of 26 lectures and contributions to the program of the International Summer School on Advanced Topics in Artificial Intelligence held in Prague, Czechoslovakia, July 6-17, 1992. The summerschool was intended for (postgraduate) students, researchers and all those who want to learn about recent progress in both theoretical and applied AI. The papers in the volume are organized into nine parts: - Introduction - Logic and logic programming - Machine learning - Planning and scheduling - Uncertainty - Second generation expert systemsand knowledge engineering - Qualitative reasoning - Neurocomputing -Natural language and interfaces"--PUBLISHER'S WEBSITE.

A Methodology for Uncertainty in Knowledge-Based Systems

Author: Kurt Weichselberger

Publisher: Lecture Notes in Artificial Intelligence

Published: 1990-03-07

Total Pages: 154

ISBN-13:

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In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.

Book Synopsis A Methodology for Uncertainty in Knowledge-Based Systems by : Kurt Weichselberger

Download or read book A Methodology for Uncertainty in Knowledge-Based Systems written by Kurt Weichselberger and published by Lecture Notes in Artificial Intelligence. This book was released on 1990-03-07 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.