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Conference Paper: Database support for probabilistic attributes and tuples

TitleDatabase support for probabilistic attributes and tuples
Authors
Issue Date2008
Citation
Proceedings - International Conference On Data Engineering, 2008, p. 1053-1061 How to Cite?
AbstractThe inherent uncertainty of data present in numerous applications such as sensor databases, text annotations, and information retrieval motivate the need to handle imprecise data at the database level. Uncertainty can be at the attribute or tuple level and is present in both continuous and discrete data domains. This paper presents a model for handling arbitrary probabilistic uncertain data (both discrete and continuous) natively at the database level. Our approach leads to a natural and efflcient representation for probabilistic data. We develop a model that is consistent with possible worlds semantics and closed under basic relational operators. This is the first model that accurately and efficiently handles both continuous and discrete uncertainty. The model is implemented in a real database system (PostgreSQL) and the effectiveness and efficiency of our approach is validated experimentally. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/93201
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorSingh, Sen_HK
dc.contributor.authorMayfield, Cen_HK
dc.contributor.authorShah, Ren_HK
dc.contributor.authorPrabhakar, Sen_HK
dc.contributor.authorHambrusch, Sen_HK
dc.contributor.authorNeville, Jen_HK
dc.contributor.authorCheng, Ren_HK
dc.date.accessioned2010-09-25T14:53:57Z-
dc.date.available2010-09-25T14:53:57Z-
dc.date.issued2008en_HK
dc.identifier.citationProceedings - International Conference On Data Engineering, 2008, p. 1053-1061en_HK
dc.identifier.issn1084-4627en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93201-
dc.description.abstractThe inherent uncertainty of data present in numerous applications such as sensor databases, text annotations, and information retrieval motivate the need to handle imprecise data at the database level. Uncertainty can be at the attribute or tuple level and is present in both continuous and discrete data domains. This paper presents a model for handling arbitrary probabilistic uncertain data (both discrete and continuous) natively at the database level. Our approach leads to a natural and efflcient representation for probabilistic data. We develop a model that is consistent with possible worlds semantics and closed under basic relational operators. This is the first model that accurately and efficiently handles both continuous and discrete uncertainty. The model is implemented in a real database system (PostgreSQL) and the effectiveness and efficiency of our approach is validated experimentally. © 2008 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofProceedings - International Conference on Data Engineeringen_HK
dc.titleDatabase support for probabilistic attributes and tuplesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailCheng, R:ckcheng@cs.hku.hken_HK
dc.identifier.authorityCheng, R=rp00074en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICDE.2008.4497514en_HK
dc.identifier.scopuseid_2-s2.0-52649155904en_HK
dc.identifier.hkuros150627en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-52649155904&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1053en_HK
dc.identifier.epage1061en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridSingh, S=14028945800en_HK
dc.identifier.scopusauthoridMayfield, C=21743283100en_HK
dc.identifier.scopusauthoridShah, R=35365088300en_HK
dc.identifier.scopusauthoridPrabhakar, S=7101672592en_HK
dc.identifier.scopusauthoridHambrusch, S=7004357219en_HK
dc.identifier.scopusauthoridNeville, J=7006145328en_HK
dc.identifier.scopusauthoridCheng, R=7201955416en_HK
dc.identifier.citeulike4487083-

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