Foundations of Fuzzy Logic and Semantic Web Languages Chapman & Hall/CRC Studies in Informatics Series

Managing vagueness/fuzziness is starting to play an important role in Semantic Web research, with a large number of research efforts underway. Foundations of Fuzzy Logic and Semantic Web Languages provides a rigorous and succinct account of the mathematical methods and tools used for representing and reasoning with fuzzy information within Semantic Web languages. The book focuses on the three main streams of Semantic Web languages:

• Triple languages RDF and RDFS
• Conceptual languages OWL and OWL 2, and their profiles OWL EL, OWL QL, and OWL RL
• Rule-based languages, such as SWRL and RIF

Written by a prominent researcher in this area, the book is the first to combine coverage of fuzzy logic and Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic.

With an extensive bibliography, this book provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages.

The Quest for Fuzzy Logic in Semantic Web Languages. SEMANTIC WEB LANGUAGES BASICS: Introduction. Resource Description Language RDF and RDF Schema. Web Ontology Language OWL. Rule Languages. Query Languages for SWL-Based Knowledge Bases. FUZZY LOGICS AND SEMANTIC WEB LANGUAGES: Introduction. Fuzzy Sets and Mathematical Fuzzy Logic Basics. Fuzzy RDF and RDFS. Fuzzy OWL. Fuzzy Rule Languages. Appendices. Bibliography.

Umberto Straccia is a researcher at the Istituto di Scienze e di Tecnologie dell’Informazione (ISTI) of the Italian National Council of Research (CNR). He received a Ph.D. in computer science from the University of Dortmund. His research interests include fuzzy logic, knowledge representation and reasoning, semantic web languages, machine learning, and decision making.