Fuzzy Knowledge Management for the Semantic Web [electronic resource] / by Zongmin Ma, Fu Zhang, Li Yan, Jingwei Cheng.
By: Ma, Zongmin [author.].
Contributor(s): Zhang, Fu [author.] | Yan, Li [author.] | Cheng, Jingwei [author.] | SpringerLink (Online service).
Material type:
BookSeries: Studies in Fuzziness and Soft Computing: 306Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XI, 275 p. 67 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642392832.Subject(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)DDC classification: 006.3 Online resources: Click here to access online Knowledge Representation and Reasoning in the Semantic Web -- Fuzzy Sets and Possibility Theory -- Fuzzy Data Models and Formal Descriptions -- Fuzzy Description Logics and Fuzzy Ontologies -- Fuzzy Description Logic and Ontology Extraction from Fuzzy Data Models -- Fuzzy Semantic Web Ontology Mapping -- Querying Fuzzy Description Logics and Ontology Knowledge Bases -- Fuzzy Ontology Knowledge Bases Storage in Fuzzy Databases -- Fuzzy Rules and Interchange in the Semantic Web.
This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the Semantic Web. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge bases in fuzzy databases, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web. The book aims to provide a single record of current research in the fuzzy knowledge representation and reasoning for the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners and graduate students of the Web intelligence and at the same time serve the knowledge and data engineering professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
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