Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/4771
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dc.contributor.authorLi, Xueheng.en_US
dc.date.accessioned2008-09-17T09:58:11Z-
dc.date.available2008-09-17T09:58:11Z-
dc.date.copyright2002en_US
dc.date.issued2002-
dc.identifier.urihttp://hdl.handle.net/10356/4771-
dc.description.abstractThe objective of this project is to propose an improved web frequent sequential patterns mining algorithm for generating analysis rules for large-scale purchase datasets. By a careful evaluation of the traditional mining algorithms, we aim to design a better algorithm that is more scalable and efficient.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems-
dc.titleFrequent sequential pattern mining for e-commerce applicationsen_US
dc.typeThesisen_US
dc.contributor.supervisorKong, Hinny Pe Hinen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Communication and Network Systems)en_US
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