Van Tham Nguyen, Ngoc Thanh Nguyen, Trong Hieu Tran

Knowledge Integration Methods for Probabilistic Knowledge-based Systems (eBook, ePUB)

• Format: ePub

Produktbeschreibung

This book provides a snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency and integrating knowledge bases. It provides the mathematical background to solve problems of restoring consistency and problems of integrating probabilistic knowledge bases.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 202
• Erscheinungstermin: 30. Dezember 2022
• Englisch
• ISBN-13: 9781000809992
• Artikelnr.: 66982421

Autorenporträt

Van Tham Nguyen is currently PhD at Thuyloi University, Hanoi, Vietnam. He received his Ph.D. degree from VNU - University of Engineering and Technology in 2022. His scientific interests consist of collective intelligence, knowledge integration methods, inconsistent knowledge processing, and machine learning. He has published nine peer-reviewed papers in journals and conference proceedings.

Ngoc Thanh Nguyen (Ph.D., D.Sc.) is a full professor and the Head of Applied Informatics Department at the Wroclaw University of Science and Technology, Poland. He is author or co-author of 6 books and over 450 papers.

Trong Hieu Tran is currently an Associate Professor at VNU - University of Engineering and Technology. He received his dual Ph.D. degree from Wroclaw University of Technology (Poland) and Swinburne University of Technology (Australia) in 2013. His research interests include belief merging, multi-agent systems, data mining and machine learning. He is the author of 21 peer-reviewed papers in reputable journals and conferences.

Inhaltsangabe

1. Introduction 2. Probabilistic Knowledge-based Systems 3. Consistency
Measures for Probabilistic Knowledge Bases 4. Methods for Restoring
Consistency in Probabilistic Knowledge Bases 5. Distance-Based Methods for
Integrating Probabilistic Knowledge Bases 6. Value-based Method for
Integrating Probabilistic Knowledge Bases 7. Experiments and Applications
8. Conclusions and Open Problems