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03725nam a22005895i 4500 |
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978-3-662-54037-4 |
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20161215111431.0 |
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|a 9783662540374
|9 978-3-662-54037-4
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|a 10.1007/978-3-662-54037-4
|2 doi
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|a QA76.9.D3
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|a UMT
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|a COM021000
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|a 005.74
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|a Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIX
|h [electronic resource] /
|c edited by Abdelkader Hameurlain, Josef Küng, Roland Wagner.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2016.
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|a VII, 135 p. 29 illus.
|b online resource.
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|a text
|b txt
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 10120
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|a 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.
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|a 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. .
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|a Computer science.
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|a Algorithms.
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|a Database management.
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|a Data mining.
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|a Information storage and retrieval.
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|a Artificial intelligence.
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|a Computer Science.
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|a Database Management.
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|a Data Mining and Knowledge Discovery.
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|a Artificial Intelligence (incl. Robotics).
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|a Information Storage and Retrieval.
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|a Information Systems Applications (incl. Internet).
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|a Algorithm Analysis and Problem Complexity.
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|a Hameurlain, Abdelkader.
|e editor.
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|a Küng, Josef.
|e editor.
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|a Wagner, Roland.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783662540367
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 10120
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|u http://dx.doi.org/10.1007/978-3-662-54037-4
|z Full Text via HEAL-Link
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|a ZDB-2-SCS
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912 |
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|a ZDB-2-LNC
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|a Computer Science (Springer-11645)
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