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Conference Paper: Adaptive stream filters for entity-based queries with non-value tolerance

TitleAdaptive stream filters for entity-based queries with non-value tolerance
Authors
KeywordsApproximation theory
Costs
Network protocols
Numerical analysis
Query languages
Issue Date2005
PublisherMorgan Kaufmann Publishers, Inc..
Citation
The 31st International Conference on Very Large Data Bases (VLDB 2005), Trondheim, Norway, 30 August-2 September 2005. In Proceedings of the 31st VLDB, 2005, v. 1, p. 37-48 How to Cite?
AbstractWe study the problem of applying adaptive niters for approximate query processing in a distributed stream environment. We propose filter bound assignment protocols with the objective of reducing communication cost. Most previous works focus on value-based queries (e.g., average) with numerical error tolerance. In this paper, we cover entity-based queries (e.g., nearest neighbor) with non-value-based error tolerance. We investigate different non-value-based error tolerance definitions and discuss how they are applied to two classes of entity-based queries: non-rank-based and rank-based queries. Extensive experiments show that our protocols achieve significant savings in both communication overhead and server computation.
DescriptionResearch Session 1: Streams and Stream-based Processing
Persistent Identifierhttp://hdl.handle.net/10722/93417
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorCheng, Ren_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorPrabhakar, Sen_HK
dc.contributor.authorKwan, Aen_HK
dc.contributor.authorTu, Yen_HK
dc.date.accessioned2010-09-25T15:00:32Z-
dc.date.available2010-09-25T15:00:32Z-
dc.date.issued2005en_HK
dc.identifier.citationThe 31st International Conference on Very Large Data Bases (VLDB 2005), Trondheim, Norway, 30 August-2 September 2005. In Proceedings of the 31st VLDB, 2005, v. 1, p. 37-48en_HK
dc.identifier.issn1047-7349-
dc.identifier.urihttp://hdl.handle.net/10722/93417-
dc.descriptionResearch Session 1: Streams and Stream-based Processing-
dc.description.abstractWe study the problem of applying adaptive niters for approximate query processing in a distributed stream environment. We propose filter bound assignment protocols with the objective of reducing communication cost. Most previous works focus on value-based queries (e.g., average) with numerical error tolerance. In this paper, we cover entity-based queries (e.g., nearest neighbor) with non-value-based error tolerance. We investigate different non-value-based error tolerance definitions and discuss how they are applied to two classes of entity-based queries: non-rank-based and rank-based queries. Extensive experiments show that our protocols achieve significant savings in both communication overhead and server computation.en_HK
dc.languageengen_HK
dc.publisherMorgan Kaufmann Publishers, Inc..-
dc.relation.ispartofProceedings of the 31st International Conference, VLDB 2005en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectApproximation theory-
dc.subjectCosts-
dc.subjectNetwork protocols-
dc.subjectNumerical analysis-
dc.subjectQuery languages-
dc.titleAdaptive stream filters for entity-based queries with non-value toleranceen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailCheng, R:ckcheng@cs.hku.hken_HK
dc.identifier.emailKao, B:kao@cs.hku.hken_HK
dc.identifier.authorityCheng, R=rp00074en_HK
dc.identifier.authorityKao, B=rp00123en_HK
dc.description.naturepostprint-
dc.identifier.scopuseid_2-s2.0-33745594862en_HK
dc.identifier.hkuros123115en_HK
dc.identifier.hkuros176486-
dc.identifier.hkuros109837-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745594862&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume1en_HK
dc.identifier.spage37en_HK
dc.identifier.epage48en_HK
dc.description.otherThe 31st International Conference on Very Large Data Bases (VLDB 2005), Trondheim, Norway, 30 August-2 September 2005. In Proceedings of the 31st VLDB, 2005, v. 1, p. 37-48-
dc.identifier.scopusauthoridCheng, R=7201955416en_HK
dc.identifier.scopusauthoridKao, B=35221592600en_HK
dc.identifier.scopusauthoridPrabhakar, S=7101672592en_HK
dc.identifier.scopusauthoridKwan, A=14028804500en_HK
dc.identifier.scopusauthoridTu, Y=7201525630en_HK

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