<P>Managing vagueness/fuzziness is starting to play an important role in Semantic Web research, with a large number of research efforts underway. <STRONG>Foundations of Fuzzy Logic and Semantic Web Languages</STRONG> provides a rigorous and succinct account of the mathematical methods and tools used
Fuzzy Logic and the Semantic Web
β Scribed by Elie Sanchez (Eds.)
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Leaves
- 489
- Series
- Capturing Intelligence 1
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
These are exciting times in the fields of Fuzzy Logic and the Semantic Web, and this book will add to the excitement, as it is the first volume to focus on the growing connections between these two fields. This book is expected to be a valuable aid to anyone considering the application of Fuzzy Logic to the Semantic Web, because it contains a number of detailed accounts of these combined fields, written by leading authors in several countries. The Fuzzy Logic field has been maturing for forty years. These years have witnessed a tremendous growth in the number and variety of applications, with a real-world impact across a wide variety of domains with humanlike behavior and reasoning. And we believe that in the coming years, the Semantic Web will be major field of applications of Fuzzy Logic.This book, the first in the new series Capturing Intelligence, shows the positive role Fuzzy Logic, and more generally Soft Computing, can play in the development of the Semantic Web, filling a gap and facing a new challenge. It covers concepts, tools, techniques and applications exhibiting the usefulness, and the necessity, for using Fuzzy Logic in the Semantic Web. It finally opens the road to new systems with a high Web IQ.Most of today's Web content is suitable for human consumption. The Semantic Web is presented as an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. For example, within the Semantic Web, computers will understand the meaning of semantic data on a web page by following links to specified ontologies. But while the Semantic Web vision and research attracts attention, as long as it will be used two-valued-based logical methods no progress will be expected in handling ill-structured, uncertain or imprecise information encountered in real world knowledge. Fuzzy Logic and associated concepts and techniques (more generally, Soft Computing), has certainly a positive role to play in the development of the Semantic Web. Fuzzy Logic will not supposed to be the basis for the Semantic Web but its related concepts and techniques will certainly reinforce the systems classically developed within W3C.In fact, Fuzzy Logic cannot be ignored in order to bridge the gap between human-understandable soft logic and machine-readable hard logic. None of the usual logical requirements can be guaranteed: there is no centrally defined format for data, no guarantee of truth for assertions made, no guarantee of consistency. To support these arguments, this book shows how components of the Semantic Web (like XML, RDF, Description Logics, Conceptual Graphs, Ontologies) can be covered, with in each case a Fuzzy Logic focus.Key features.- First volume to focus on the growing connections between Fuzzy Logic and the Semantic Web. - Keynote chapter by Lotfi Zadeh. - The Semantic Web is presently expected to be a major field of applications of Fuzzy Logic. - It fills a gap and faces a new challenge in the development of the Semantic Web. - It opens the road to new systems with a high Web IQ. - Contributed chapters by Fuzzy Logic leading experts. - First volume to focus on the growing connections between Fuzzy Logic and the Semantic Web. - Keynote chapter by Lotfi Zadeh. - The Semantic Web is presently expected to be a major field of applications of Fuzzy Logic. - It fills a gap and faces a new challenge in the development of the Semantic Web. - It opens the road to new systems with a high Web IQ. - Contributed chapters by Fuzzy Logic leading experts.
β¦ Table of Contents
Content:
Preface
Page vii
Frank van Harmelen
Foreword: Fuzzy logic in the semantic web: Covering a missing link
Pages ix-xiii
Elie Sanchez
Chapter 1 On the expressiveness of the languages for the semantic web β Making a case for βa little moreβ Original Research Article
Pages 3-20
Christopher Thomas, Amit Sheth
Chapter 2 Fuzzy ontologies for information retrieval on the WWW Original Research Article
Pages 21-48
David Parry
Chapter 3 Capturing basic semantics exploiting RDF-oriented classification Original Research Article
Pages 49-69
Vincenzo Loia, Sabrina Senatore
Chapter 4 A fuzzy description logic for the semantic web Original Research Article
Pages 73-90
Umberto Straccia
Chapter 5 What does mathematical fuzzy logic offer to description logic? Original Research Article
Pages 91-100
Petr HΓ‘jek
Chapter 6 Possibilistic uncertainty and fuzzy features in description logic. A preliminary discussion Original Research Article
Pages 101-113
Didier Dubois, JΓ©rΓ΄me Mengin, Henri Prade
Chapter 7 Uncertainty and description logic programs over lattices Original Research Article
Pages 115-133
Umberto Straccia
Chapter 8 Fuzzy quantification in fuzzy description logics Original Research Article
Pages 135-159
Daniel SΓ‘nchez, Andrea G.B. Tettamanzi
Chapter 9 From search engines to question answering systems β The problems of world knowledge, relevance, deduction and precisiation Original Research Article
Pages 163-210
Lotfi A. Zadeh
Chapter 10 A perception-based web search with fuzzy semantic Original Research Article
Pages 211-230
Chris Tseng, Toan Vu
Chapter 11 Using knowledge trees for semantic web querying Original Research Article
Pages 231-246
Ronald R. Yager
Chapter 12 Fuzzy data mining for the semantic web: Building XML mediator schemas Original Research Article
Pages 249-264
A. Laurent, M. Teisseire, P. Poncelet
Chapter 13 Bottom-up extraction and maintenance of ontology-based metadata Original Research Article
Pages 265-282
Paolo Ceravolo, Angelo Corallo, Ernesto Damiani, Gianluca Elia, Marco Viviani, Antonio Zilli
Chapter 14 Approximate knowledge graph retrieval: Measures and realization Original Research Article
Pages 283-304
T.H. Cao, Dat T. Huynh
Chapter 15 Soft integration of information with semantic gaps Original Research Article
Pages 307-326
Trevor Martin, Ben Azvine
Chapter 16 Processing fuzzy information in semantic web applications Original Research Article
Pages 327-339
Sebastian Kloeckner, Klaus Turowski, Uwe Weng
Chapter 17 Fuzzy logic aggregation for semantic web search for the best (top-k) answer Original Research Article
Pages 341-359
Peter VojtΓ‘Ε‘
Chapter 18 A fuzzy logic approach to information retrieval using an ontology-based representation of documents Original Research Article
Pages 363-377
Mustapha Baziz, Mohand Boughanem, Henri Prade, Gabriella Pasi
Chapter 19 Towards a semantic portal for oncology using a description logic with fuzzy concrete domains Original Research Article
Pages 379-393
Mathieu d'Aquin, Jean Lieber, Amedeo Napoli
Chapter 20 Fuzzy relational ontological model in information search systems Original Research Article
Pages 395-412
Rachel Pereira, Ivan Ricarte, Fernando Gomide
Chapter 21 Evolving ontologies for intelligent decision support Original Research Article
Pages 415-439
Paulo Gottgtroy, Nikola Kasabov, Stephen MacDonell
Chapter 22 Enhancing the power of the internet using fuzzy logic-based web intelligence: Beyond the semantic web Original Research Article
Pages 441-464
Masoud Nikravesh
Author index
Pages 465-473
Subject index
Pages 475-479
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