Fuzzy computational ontologies in contexts: formal models of knowledge representation with membership degree and typicality of objects, and their applications

Knowledge Representation plays an essential role in Semantic Web, in particular in automated information processing and communications among software agents. This book, entitled 'Fuzzy Computational Ontologies in Contexts: Formal Models of Knowledge Representation with Membership Degree and Typicality, and Their Applications', discusses knowledge representation in Semantic Web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies. The book is intended for graduate students, engineers, and researchers in the field of artificial intelligence and computer science. Yi Cai is an Assistant Professor in School of Software Engineering, South China University of Technology, Guangzhou, China. Ching-man Au Yeung is a Senior Engineer in Hong Kong Applied Science and Technology Research Institute, Hong Kong, China. Ho-fung Leung is a Professor and the Chairman of Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China. First attempt to incorporate object membership and typicality in computational ontologies. Application in recommender systems. Multiple illustrating examples. INDICE: Introduction. Knowledge Representation on the Web. Concepts and Categorization From a Psychological Perspective. Modeling Uncertainty in Knowledge Representation. Fuzzy Ontology: A First Formal Model. A more General Ontology Model with Object Membership and Typicality. Context-aware Object Typicality Measurement in Fuzzy Ontology. Object Membership with Property Importance and Property Priority. Applications. Conclusions and Future Work.

• ISBN: 978-3-642-25455-0
• Editorial: Springer Berlin Heidelberg
• Encuadernacion: Cartoné
• Páginas: 199
• Fecha Publicación: 31/01/2012
• Nº Volúmenes: 1
• Idioma: Inglés