Fuzzy Knowledge Management for the Semantic Web

This comprehensive technical guide explores the integration of fuzzy logic technologies with Semantic Web frameworks, offering in-depth coverage of fuzzy description logics, ontology development, and knowledge base management. The book systematically addresses how fuzzy approaches can enhance traditional Semantic Web architectures, covering everything from extracting fuzzy description logics from data models to storing fuzzy ontology knowledge bases in specialized databases. It provides thorough technical treatment of fuzzy ontology mapping and rule interchange mechanisms that bridge the gap between precise semantic structures and real-world uncertainty.

What distinguishes this work is its practical approach to implementing fuzzy knowledge management systems within Semantic Web environments, making it particularly valuable for researchers and developers working on artificial intelligence applications that require handling imprecise or uncertain data. The book's systematic treatment of fuzzy rule interchange and ontology mapping provides concrete methodologies for professionals building intelligent systems that need to process ambiguous or incomplete information. For those developing next-generation semantic technologies that must operate in messy real-world contexts, this volume offers both theoretical foundations and practical implementation strategies.