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dc.contributor.authorLi, HFen_US
dc.contributor.authorLee, SYen_US
dc.contributor.authorShan, MKen_US
dc.date.accessioned2014-12-08T15:18:41Z-
dc.date.available2014-12-08T15:18:41Z-
dc.date.issued2005-08-01en_US
dc.identifier.issn0167-8655en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.patrec.2005.01.016en_US
dc.identifier.urihttp://hdl.handle.net/11536/13438-
dc.description.abstractIn this paper, we address the problem of online mining maximal frequent structures (Type I & II melody structures) in unbounded, continuous landmark melody streams. An efficient algorithm, called MMSLMS (Maximal Melody Structures of Landmark Melody Streams), is developed for online incremental mining of maximal frequent melody substructures in one scan of the continuous melody streams. In MMSLMS, a space-efficient scheme, called CMB (Chord-set Memory Border), is proposed to constrain the upper-bound of space requirement of maximal frequent melody structures in such a streaming environment. Theoretical analysis and experimental study show that our algorithm is efficient and scalable for mining the set of all maximal melody structures in a landmark melody stream. (c) 2005 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectmachine learningen_US
dc.subjectdata miningen_US
dc.subjectlandmark melody streamen_US
dc.subjectmaximal melody structureen_US
dc.subjectOnline algorithmen_US
dc.titleOnline mining maximal frequent structures in continuous landmark melody streamsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.patrec.2005.01.016en_US
dc.identifier.journalPATTERN RECOGNITION LETTERSen_US
dc.citation.volume26en_US
dc.citation.issue11en_US
dc.citation.spage1658en_US
dc.citation.epage1674en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000230052300006-
dc.citation.woscount9-
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