SPARQL Query Optimization using Nature Inspired Algorithms - Ramalingam, Gomathi;Dhandapani, Sharmila
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The emergence of multiple web pages day by day leads to the development of the Semantic Web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the Resource Description Framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving meta-heuristic algorithms become an alternate to the traditional query optimization methods. This book focuses on the problem of query optimization of semantic web data. An efficient nature inspired algorithm called Adaptive Cuckoo Search (ACS) for querying and generating optimal query plan for large RDF graphs is discussed in this book.…mehr

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Produktbeschreibung
The emergence of multiple web pages day by day leads to the development of the Semantic Web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the Resource Description Framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving meta-heuristic algorithms become an alternate to the traditional query optimization methods. This book focuses on the problem of query optimization of semantic web data. An efficient nature inspired algorithm called Adaptive Cuckoo Search (ACS) for querying and generating optimal query plan for large RDF graphs is discussed in this book.
Autorenporträt
Dr. R. Gomathi completed her B.E(CSE) in Periyar University in 2003 and M.E(CSE) in Anna University in 2011.She has completed her PhD in Anna University, Chennai during 2016 and at present, she is working as an Assistant Professor(Sr.G) in the Department of Computer Science and Engineering at Bannari Amman Institute of Technology, Sathyamangalam.