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Conference Paper: A comparison study on algorithms for incremental update of frequent sequences

TitleA comparison study on algorithms for incremental update of frequent sequences
Authors
KeywordsData mining
Incremental update
Sequence
Issue Date2002
PublisherIEEE, Computer Society.
Citation
Proceedings - Ieee International Conference On Data Mining, Icdm, 2002, p. 554-561 How to Cite?
AbstractThe problem of mining frequent sequences is to extract frequently occurring subsequences in a sequence database. Algorithms on this mining problem include GSP, MFS, and SPADE. The problem of incremental update of frequent sequences is to keep track of the set of frequent sequences as the underlying database changes. Previous studies have extended the traditional algorithms to efficiently solve the update problem. These incremental algorithms include ISM, GSP+ and MFS+. Each incremental algorithm has its own characteristics and they have been studied and evaluated separately under different scenarios. This paper presents a comprehensive study on the relative performance of the incremental algorithms as well as their non-incremental counterparts. Our goal is to provide guidelines on the choice of an algorithm for solving the incremental update problem given the various characteristics of a sequence database. © 2002 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/53601
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorZhang, Men_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorYip, CLen_HK
dc.date.accessioned2009-04-03T07:24:21Z-
dc.date.available2009-04-03T07:24:21Z-
dc.date.issued2002en_HK
dc.identifier.citationProceedings - Ieee International Conference On Data Mining, Icdm, 2002, p. 554-561en_HK
dc.identifier.issn1550-4786en_HK
dc.identifier.urihttp://hdl.handle.net/10722/53601-
dc.description.abstractThe problem of mining frequent sequences is to extract frequently occurring subsequences in a sequence database. Algorithms on this mining problem include GSP, MFS, and SPADE. The problem of incremental update of frequent sequences is to keep track of the set of frequent sequences as the underlying database changes. Previous studies have extended the traditional algorithms to efficiently solve the update problem. These incremental algorithms include ISM, GSP+ and MFS+. Each incremental algorithm has its own characteristics and they have been studied and evaluated separately under different scenarios. This paper presents a comprehensive study on the relative performance of the incremental algorithms as well as their non-incremental counterparts. Our goal is to provide guidelines on the choice of an algorithm for solving the incremental update problem given the various characteristics of a sequence database. © 2002 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE, Computer Society.en_HK
dc.relation.ispartofProceedings - IEEE International Conference on Data Mining, ICDMen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectData miningen_HK
dc.subjectIncremental updateen_HK
dc.subjectSequenceen_HK
dc.titleA comparison study on algorithms for incremental update of frequent sequencesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailKao, B:kao@cs.hku.hken_HK
dc.identifier.emailYip, CL:clyip@cs.hku.hken_HK
dc.identifier.authorityKao, B=rp00123en_HK
dc.identifier.authorityYip, CL=rp00205en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICDM.2002.1184001en_HK
dc.identifier.scopuseid_2-s2.0-70349583815en_HK
dc.identifier.hkuros93355-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349583815&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage554en_HK
dc.identifier.epage561en_HK
dc.identifier.scopusauthoridZhang, M=8533032400en_HK
dc.identifier.scopusauthoridKao, B=35221592600en_HK
dc.identifier.scopusauthoridYip, CL=7101665547en_HK

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