GrouPeer: A system for clustering PDMSs

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dc.contributor.author Kantere, V en
dc.contributor.author Bousounis, D en
dc.contributor.author Sellis, T en
dc.date.accessioned 2014-03-01T02:02:19Z
dc.date.available 2014-03-01T02:02:19Z
dc.date.issued 2011 en
dc.identifier.issn 21508097 en
dc.identifier.uri http://hdl.handle.net/123456789/29301
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-84863746342&partnerID=40&md5=59011e5a60a66f851610cc3577816e56 en
dc.subject.other Approximate query en
dc.subject.other Clustering mechanism en
dc.subject.other Dynamic clustering en
dc.subject.other High quality en
dc.subject.other Iterative learning process en
dc.subject.other Local information en
dc.subject.other Propagation paths en
dc.subject.other Query similarity en
dc.subject.other Schema matching en
dc.subject.other Semantic clustering en
dc.subject.other Structured data en
dc.subject.other Degradation en
dc.subject.other Query processing en
dc.subject.other Semantics en
dc.subject.other Search engines en
dc.title GrouPeer: A system for clustering PDMSs en
heal.type journalArticle en
heal.publicationDate 2011 en
heal.abstract Sharing structured data in a PDMS is hard due to schema heterogeneity and peer autonomy. To overcome heterogeneity, peer databases employ mappings that partially match local information to that of their direct neighbors. Traditionally, a query is successively rewritten along the propagation path on each peer. This results in gradual query degradation and the inability to retrieve data pertinent to the original version, even from peers that store such data. This demonstration presents GrouPeer, a system that overcomes the query degradation problem and enables the dynamic clustering of the overlay according to the semantics of the peer data, utilizing normal query traffic. Peers are provided with a methodology that allows them to choose which rewritten version of a query to answer and discover remote information-rich sources. The demonstration illustrates the functionalities in the clustering mechanism of GrouPeer: approximate query rewriting, query similarity methodology, construction of new mappings, iterative learning process, employment of automatic schema matching, and proves the capability of the system to perform gradual semantic clustering and enable high quality answers to peer queries. © 2011 VLDB Endowment. en
heal.journalName Proceedings of the VLDB Endowment en
dc.identifier.volume 4 en
dc.identifier.issue 12 en
dc.identifier.spage 1371 en
dc.identifier.epage 1374 en

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