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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIX 1st ed. 2016 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 135 pages, height x width: 235x155 mm, weight: 2292 g, 29 Illustrations, black and white; VII, 135 p. 29 illus., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 10120
  • Izdošanas datums: 23-Dec-2016
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3662540363
  • ISBN-13: 9783662540367
  • Mīkstie vāki
  • Cena: 46,91 €*
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  • Formāts: Paperback / softback, 135 pages, height x width: 235x155 mm, weight: 2292 g, 29 Illustrations, black and white; VII, 135 p. 29 illus., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 10120
  • Izdošanas datums: 23-Dec-2016
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3662540363
  • ISBN-13: 9783662540367
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments.This, the

29th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four revised selected regular papers. Topics covered include optimization and cluster validation processes for entity matching, business intelligence systems, and data profiling in the Semantic Web.

Sensitivity- An Important Facet of Cluster Validation Process for Entity Matching Technique.- Pay-as-You-Go Configuration of Entity Resolution.- A Unified View of Data-Intensive Flows in Business Intelligence Systems: A Survey.- A Self-Adaptive and Incremental Approach for Data Profiling in the Semantic Web.

Sensitivity- An Important Facet of Cluster Validation Process for Entity Matching Technique.- Pay-as-You-Go Configuration of Entity Resolution.- A Unified View of Data-Intensive Flows in Business Intelligence Systems: A Survey.- A Self-Adaptive and Incremental Approach for Data Profiling in the Semantic Web.