Read and Download eBook Full
Author: Zongmin Ma
Publisher: IGI Global
Published: 2005-01-01
Total Pages: 362
ISBN-13: 9781591403852
DOWNLOAD EBOOKReaders will get a complete understanding of the notions, techniques, and methods related to the research and developments of fuzzy object-oriented databases from the book, which will serve as a starting point and a reference for their research and developments."--BOOK JACKET.
Author: Mehdi Khosrow-Pour
Publisher: IGI Global Snippet
Published: 2009
Total Pages: 4292
ISBN-13: 9781605660264
DOWNLOAD EBOOK"This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.
Author: Erickson, John
Publisher: IGI Global
Published: 2009-02-28
Total Pages: 2962
ISBN-13: 1605660590
DOWNLOAD EBOOK"This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals"--Provided by publisher.
Author: Zongmin Ma
Publisher: IGI Global
Published: 2007-01-01
Total Pages: 335
ISBN-13: 1599041200
DOWNLOAD EBOOK"This book integrates data management in databases with intelligent data processing and analysis in artificial intelligence. It challenges today's database technology and promotes its evolution"--Provided by publisher.
Author: Zongmin Ma
Publisher: Springer Nature
Published: 2022-09-08
Total Pages: 217
ISBN-13: 3031116690
DOWNLOAD EBOOKThis 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.
Author: Wang, John
Publisher: IGI Global
Published: 2008-05-31
Total Pages: 4092
ISBN-13: 159904952X
DOWNLOAD EBOOKIn recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
Author: Zongmin Ma
Publisher: Springer
Published: 2013-03-30
Total Pages: 167
ISBN-13: 364237509X
DOWNLOAD EBOOKThis 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.
Author: Rivero, Laura C.
Publisher: IGI Global
Published: 2005-06-30
Total Pages: 784
ISBN-13: 1591407958
DOWNLOAD EBOOK"Addresses the evolution of database management, technologies and applications along with the progress and endeavors of new research areas."--P. xiii.
Author: Zongmin Ma
Publisher: Springer Science & Business Media
Published: 2006-06-15
Total Pages: 222
ISBN-13: 038724249X
DOWNLOAD EBOOKFuzzy 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. Secondly, 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.
Author: Li Yan
Publisher: Springer
Published: 2013-11-25
Total Pages: 218
ISBN-13: 3642448992
DOWNLOAD EBOOKThis 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.
