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Improving source selection in large scale mediation systems through combinatorial optimization techniques

  • Institut polytechnique de Grenoble
  • Universidad de los Andes Colombia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper concerns querying in large scale virtual organizations. Such organizations are characterized by a challenging data context involving a large number of distributed data sources with strong heterogeneity and uncontrolled data overlapping. In that context, data source selection during query evaluation is particularly important and complex. To cope with this task, we propose OptiSource, an original strategy for source selection using combinatorial optimization techniques combined to organizational knowledge of the virtual organization. Experiment numerical results show that OptiSource is a robust strategy that improves the precision and the recall of the source selection process. This paper presents the data and knowledge models, the definition of OptiSource, the related mathematical model, the prototype and an extensive experimental study.

Original languageEnglish
Title of host publicationTransactions on Large-Scale Data- and Knowledge-Centered Systems III - Special Issue on Data and Knowledge Management in Grid and P2P Systems
Pages138-166
Number of pages29
DOIs
StatePublished - 2011
Event3rd International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2010 - Bilbao, Spain
Duration: 01 Sep 201002 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6790 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2010
Country/TerritorySpain
CityBilbao
Period01/09/1002/09/10

Keywords

  • Combinatorial Optimization
  • Large Scale Data Mediation
  • Source Selection

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