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Conference Paper: Supporting ranking pattern-based aggregate queries in sequence data cubes

TitleSupporting ranking pattern-based aggregate queries in sequence data cubes
Authors
KeywordsTop-k
Sequence
Query processing
OLAP
Data cube
Issue Date2009
PublisherACM.
Citation
The 18th ACM Conference on Information and Knowledge Management (CIKM'09), Hong Kong, 2-6 November 2009. In Proceedings of the 18th ACM CIKM, 2009, p. 997-1006 How to Cite?
AbstractSequence data processing has been studied extensively in the literature. In recent years, the warehousing and online-analytical processing (OLAP) of archived sequence data have received growing attentions. In particular, the concept of sequence OLAP is recently proposed with the objective of evaluating various kinds of so-called Pattern-Based Aggregate (PBA) queries so that various kinds of data analytical tasks on sequence data can be carried out efficiently. This paper studies the evaluation of ranking PBA queries, which rank the results of PBA queries and return only the top-ranked ones to users. We discuss how ranking PBA queries drastically improve the usability of S-OLAP systems and present techniques that can evaluate various kinds of ranking PBA queries efficiently. Copyright 2009 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/93434
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorChui, CKen_HK
dc.contributor.authorLo, Een_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorHo, WSen_HK
dc.date.accessioned2010-09-25T15:01:02Z-
dc.date.available2010-09-25T15:01:02Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 18th ACM Conference on Information and Knowledge Management (CIKM'09), Hong Kong, 2-6 November 2009. In Proceedings of the 18th ACM CIKM, 2009, p. 997-1006en_HK
dc.identifier.isbn978-1-60558-512-3-
dc.identifier.urihttp://hdl.handle.net/10722/93434-
dc.description.abstractSequence data processing has been studied extensively in the literature. In recent years, the warehousing and online-analytical processing (OLAP) of archived sequence data have received growing attentions. In particular, the concept of sequence OLAP is recently proposed with the objective of evaluating various kinds of so-called Pattern-Based Aggregate (PBA) queries so that various kinds of data analytical tasks on sequence data can be carried out efficiently. This paper studies the evaluation of ranking PBA queries, which rank the results of PBA queries and return only the top-ranked ones to users. We discuss how ranking PBA queries drastically improve the usability of S-OLAP systems and present techniques that can evaluate various kinds of ranking PBA queries efficiently. Copyright 2009 ACM.en_HK
dc.languageengen_HK
dc.publisherACM.-
dc.relation.ispartofProceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM 2009)en_HK
dc.subjectTop-ken_HK
dc.subjectSequenceen_HK
dc.subjectQuery processingen_HK
dc.subjectOLAPen_HK
dc.subjectData cubeen_HK
dc.titleSupporting ranking pattern-based aggregate queries in sequence data cubesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChui, CK: ckchui@cs.hku.hken_HK
dc.identifier.emailLo, E: ericlo@comp.polyu.edu.hken_HK
dc.identifier.emailKao, B: kao@cs.hku.hk-
dc.identifier.emailHo, WS: wsho@cs.hku.hk-
dc.identifier.authorityKao, B=rp00123en_HK
dc.identifier.authorityHo, WS=rp01730en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1145/1645953.1646081en_HK
dc.identifier.scopuseid_2-s2.0-74549217299en_HK
dc.identifier.hkuros161671en_HK
dc.identifier.hkuros200230-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-74549217299&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage997en_HK
dc.identifier.epage1006en_HK
dc.publisher.placeUnited States-
dc.identifier.scopusauthoridHo, WS=7402968940en_HK
dc.identifier.scopusauthoridKao, B=35221592600en_HK
dc.identifier.scopusauthoridLo, E=14028731900en_HK
dc.identifier.scopusauthoridChui, CK=21741958100en_HK
dc.customcontrol.immutablesml 130524-

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