Knowledge Integration Methods For Probabilistic Knowledge Based Systems
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Knowledge Integration Methods for Probabilistic Knowledge based Systems
Author | : Van Tham Nguyen,Ngoc Thanh Nguyen,Trong Hieu Tran |
Publsiher | : CRC Press |
Total Pages | : 176 |
Release | : 2022-12-30 |
Genre | : Business & Economics |
ISBN | : 9781000809992 |
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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.
Probabilistic Graphical Models
Author | : Linda C. van der Gaag,Ad J. Feelders |
Publsiher | : Springer |
Total Pages | : 609 |
Release | : 2014-09-11 |
Genre | : Computers |
ISBN | : 9783319114330 |
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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.
Computational Collective Intelligence
Author | : Ngoc Thanh Nguyen,Elias Pimenidis,Zaheer Khan,Bogdan Trawiński |
Publsiher | : Springer |
Total Pages | : 578 |
Release | : 2018-08-27 |
Genre | : Computers |
ISBN | : 9783319984438 |
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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.
Uncertain Information Processing In Expert Systems
Author | : Petr Hajek,Tomas Havranek,Radim Jirousek |
Publsiher | : CRC Press |
Total Pages | : 310 |
Release | : 1992-06-29 |
Genre | : Computers |
ISBN | : 0849363683 |
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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.
Utilizing Data and Knowledge Mining for Probabilistic Knowledge Bases
![Utilizing Data and Knowledge Mining for Probabilistic Knowledge Bases](https://youbookinc.com/wp-content/themes/schema-lite/cover.jpg)
Author | : Daniel Joseph Stein |
Publsiher | : Unknown |
Total Pages | : 68 |
Release | : 1996-12-01 |
Genre | : Knowledge acquisition (Expert systems) |
ISBN | : OCLC:36151481 |
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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.
Uncertainty Models for Knowledge based Systems
Author | : Irwin R. Goodman,Hung T. Nguyen |
Publsiher | : North Holland |
Total Pages | : 674 |
Release | : 1985 |
Genre | : Computers |
ISBN | : UOM:39015009806368 |
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A Methodology for Uncertainty in Knowledge Based Systems
Author | : Kurt Weichselberger,Sigrid Pohlmann |
Publsiher | : Unknown |
Total Pages | : 320 |
Release | : 2014-01-15 |
Genre | : Electronic Book |
ISBN | : 366217085X |
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Artificial Intelligence Abstracts
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 448 |
Release | : 1991 |
Genre | : Artificial intelligence |
ISBN | : UOM:39015023295200 |
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