Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5327)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Included in the following conference series:
Conference proceedings info: URSW 2005. URSW 2006. URSW 2007.
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Table of contents (22 papers)
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Probabilistic and Dempster-Shafer Models
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Fuzzy and Possibilistic Models
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Inductive Reasoning and Machine Learning
Other volumes
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Uncertainty Reasoning for the Semantic Web I
Keywords
About this book
This book constitutes the thoroughly refereed first three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2005, 2006, and 2007.
The 22 papers presented are revised and strongly extended versions of selected workshops papers as well as invited contributions from leading experts in the field and closely related areas. The present volume represents the first comprehensive compilation of state-of-the-art research approaches to uncertainty reasoning in the context of the semantic Web, capturing different models of uncertainty and approaches to deductive as well as inductive reasoning with uncertain formal knowledge.
Editors and Affiliations
Bibliographic Information
Book Title: Uncertainty Reasoning for the Semantic Web I
Book Subtitle: ISWC International Workshop, URSW 2005-2007, Revised Selected and Invited Papers
Editors: Paulo Cesar G. Costa, Claudia d’Amato, Nicola Fanizzi, Kathryn B. Laskey, Kenneth J. Laskey, Thomas Lukasiewicz, Matthias Nickles, … Michael Pool
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-540-89765-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Softcover ISBN: 978-3-540-89764-4Published: 02 December 2008
eBook ISBN: 978-3-540-89765-1Published: 30 November 2008
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XIV, 403
Topics: Artificial Intelligence, Computer Science, general, Programming Techniques, Models and Principles, Probability and Statistics in Computer Science, Math Applications in Computer Science