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dc.contributor.authorZida, Souleymaneen_US
dc.contributor.authorFournier-Viger, Philippeen_US
dc.contributor.authorWu, Cheng-Weien_US
dc.contributor.authorLin, Jerry Chun-Weien_US
dc.contributor.authorTseng, Vincent S.en_US
dc.date.accessioned2016-03-28T00:05:41Z-
dc.date.available2016-03-28T00:05:41Z-
dc.date.issued2015-01-01en_US
dc.identifier.isbn978-3-319-21024-7; 978-3-319-21023-0en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-319-21024-7_11en_US
dc.identifier.urihttp://hdl.handle.net/11536/129757-
dc.description.abstractHigh-utility pattern mining is an important data mining task having wide applications. It consists of discovering patterns generating a high profit in databases. Recently, the task of high-utility sequential pattern mining has emerged to discover patterns generating a high profit in sequences of customer transactions. However, a well-known limitation of sequential patterns is that they do not provide a measure of the confidence or probability that they will be followed. This greatly hampers their usefulness for several real applications such as product recommendation. In this paper, we address this issue by extending the problem of sequential rule mining for utility mining. We propose a novel algorithm named HUSRM (High-Utility Sequential Rule Miner), which includes several optimizations to mine high-utility sequential rules efficiently. An extensive experimental study with four datasets shows that HUSRM is highly efficient and that its optimizations improve its execution time by up to 25 times and its memory usage by up to 50 %.en_US
dc.language.isoen_USen_US
dc.subjectPattern miningen_US
dc.subjectHigh-utility miningen_US
dc.subjectSequential rulesen_US
dc.titleEfficient Mining of High-Utility Sequential Rulesen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1007/978-3-319-21024-7_11en_US
dc.identifier.journalMACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, MLDM 2015en_US
dc.citation.volume9166en_US
dc.citation.spage157en_US
dc.citation.epage171en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000364839900012en_US
dc.citation.woscount1en_US
Appears in Collections:Conferences Paper