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This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with XML. The topics covered include representation of fuzzy spatiotemporal XML data, topological relationship determination for fuzzy spatiotemporal XML data, mapping between the fuzzy spatiotemporal relational database model and fuzzy spatiotemporal XML data model, and consistencies in fuzzy spatiotemporal XML data updating. Offering a comprehensive guide to the latest research on fuzzy spatiotemporal XML data management, the book is intended to provide state-of-the-art information for researchers, practitioners, and graduate students of Web intelligence, as well as data and knowledge engineering professionals confronted with non-traditional applications that make the use of conventional approaches difficult or impossible.

This book presents an exhaustive and timely review of key research work on fuzzy XML data management, and provides readers with a comprehensive resource on the state-of-the art tools and theories in this fast growing area. Topics covered in the book include: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models, reengineering of fuzzy XML into fuzzy database models, and reasoning of fuzzy XML. The book is intended as a reference guide for researchers, practitioners and graduate students working and/or studying in the field of Web Intelligence, as well as for data and knowledge engineering professionals seeking new approaches to replace traditional methods, which may be unnecessarily complex or even unproductive.

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.

This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.

Being the de-facto standard for data representation and exchange over the Web, XML (Extensible Markup Language) allows the easy development of applications that exchange data over the Web. This creates a set of data management requirements involving XML. XML and related standards have been extensively applied in many business, service, and multimedia applications. As a result, a large volume of data is managed today directly in XML format. With the wide and in-depth utilization of XML in diverse application domains, some particularities of data management in concrete applications emerge, which challenge current XML technology. This is very similar with the situation that some database models and special database systems have been developed so that databases can satisfy the need of managing diverse data well. In data- and knowledge- intensive application systems, one of the challenges can be generalized as the need to handle imprecise and uncertain information in XML data management by applying fuzzy logic, probability, and more generally soft computing. Currently, two kinds of situations are roughly identified in soft computing for XML data management: applying soft computing for the intelligent processing of classical XML data; applying soft computing for the representation and processing of imprecise and uncertain XML data. For the former, soft computing can be used for flexible query of XML document as well as XML data mining, XML duplicate detection, and so on.