Bøger af Zongmin Ma

This book systemically presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.

Fuzzy Database Modeling with XML aims to provide a single record of current research and practical applications in the fuzzy databases.   This volume is the outgrowth of research the author has conducted in recent years.  Fuzzy Database Modeling with XML introduces state of the art information to the database research, while at the same time serving the information technology professional faced with a non-traditional application that defeats conventional approaches. The research on fuzzy conceptual models and fuzzy object-oriented databases is receiving increasing attention, in addition to fuzzy relational database models.   With rapid advances in network and internet techniques as well, the databases have been applied under the environment of distributed information systems.  It is essential in this case to integrate multiple fuzzy database systems. Since databases are commonly employed to store and manipulate XML data, additional requirements are necessary to model fuzzy information with XML. Second, this book maps fuzzy XML model to the fuzzy databases.  Very few efforts at investigating these issues have thus far occurred. Fuzzy Database Modeling with XML is designed for a professional audience of researchers and practitioners in industry.   This book is also suitable for graduate-level students in computer science.

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.

This book details recent advances in fuzzy XML data management. Coverage includes: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models and reasoning of fuzzy XML.

This book explores the technologies and approaches of fuzzy logic in the Semantic Web. Coverage includes fuzzy description logics and fuzzy ontologies, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web.

Provides a record of research and practical applications in the field of intelligent databases. This book integrates data management in databases with intelligent data processing and analysis in artificial intelligence. It challenges the database technology and promotes its evolution.

Aims to provide a record of research and practical applications in the fuzzy databases. This book provides information on the database research, and is intended for a professional audience of researchers and practitioners in industry. It is also suitable for graduate-level students in computer science.

Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema.