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024 7 _a10.1007/978-3-662-46335-2
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245 1 0 _aTransactions on Large-Scale Data- and Knowledge-Centered Systems XVII
_h[electronic resource] :
_bSelected Papers from DaWaK 2013 /
_cedited by Abdelkader Hameurlain, Josef Küng, Roland Wagner, Ladjel Bellatreche, Mukesh Mohania.
250 _a1st ed. 2015.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2015.
300 _aXIII, 129 p. 57 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aTransactions on Large-Scale Data- and Knowledge-Centered Systems,
_x2510-4942 ;
_v8970
505 0 _aData Warehouse Processing Scale-Up for Massive Concurrent Queries with SPIN -- An Uncoupled Data Process and Transfer Model for Map Reduce -- Enhanced Fast Causal Network Inference over Event Streams -- Learning Through Non-linearly Supervised Dimensionality Reduction -- Metrics for Association Rule Clustering Assessment.
520 _aThe 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 17th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of five papers, selected from the 24 full and 8 short papers presented at the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013, held in Prague, The Czech Republic, in August 2013. Of the five papers, two cover data warehousing aspects related to query processing optimization in advanced platforms, specifically Map Reduce and parallel databases, and three cover knowledge discovery, specifically the causal network inference problem, dimensionality reduction, and the quality-of-pattern-mining task.
650 0 _aDatabase management.
_93157
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aAlgorithms.
_93390
650 1 4 _aDatabase Management.
_93157
650 2 4 _aData Mining and Knowledge Discovery.
_9163611
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aAlgorithms.
_93390
700 1 _aHameurlain, Abdelkader.
_eeditor.
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700 1 _aKüng, Josef.
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_9163613
700 1 _aWagner, Roland.
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_9163614
700 1 _aBellatreche, Ladjel.
_eeditor.
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_9163615
700 1 _aMohania, Mukesh.
_eeditor.
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_9163616
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aTransactions on Large-Scale Data- and Knowledge-Centered Systems,
_x2510-4942 ;
_v8970
_9163618
856 4 0 _uhttps://doi.org/10.1007/978-3-662-46335-2
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