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Transactions on Large-Scale Data- and Knowledge-Centered Systems XIII [electronic resource] /

Contributor(s): Material type: TextTextSeries: Transactions on Large-Scale Data- and Knowledge-Centered Systems ; 8420Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Edition: 1st ed. 2014Description: IX, 187 p. 72 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642544262
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.74 23
LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Enabling a Package Query Paradigm on the Semantic Web: Model and Algorithms -- SemLAV: Local-as-View Mediation for SPARQL Queries -- Query Reformulation in PDMS Based on Social Relevance -- Distributed Large-Scale Information Filtering -- RUBIK: Proactive, Entity-Centric and Personalized Situational Web Application Design -- Mining Multiple Related Data Sources Using Object-Oriented Models.
In: Springer Nature eBookSummary: 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 13th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include federated data sources, information filtering, web data clouding, query reformulation, package skyline queries and SPARQL query processing over a LaV (Local-as-View) integration system.
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Enabling a Package Query Paradigm on the Semantic Web: Model and Algorithms -- SemLAV: Local-as-View Mediation for SPARQL Queries -- Query Reformulation in PDMS Based on Social Relevance -- Distributed Large-Scale Information Filtering -- RUBIK: Proactive, Entity-Centric and Personalized Situational Web Application Design -- Mining Multiple Related Data Sources Using Object-Oriented Models.

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 13th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include federated data sources, information filtering, web data clouding, query reformulation, package skyline queries and SPARQL query processing over a LaV (Local-as-View) integration system.

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