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DSM-TKP: Mining Top-K Path traversal patterns over Web click-streams

dc.citation.epage329en_US
dc.citation.spage326en_US
dc.contributor.authorLi, HFen_US
dc.contributor.authorLee, SYen_US
dc.contributor.authorShan, MKen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:25:38Z
dc.date.available2014-12-08T15:25:38Z
dc.date.issued2005en_US
dc.description.abstractOnline, single-pass mining Web click streams poses some interesting computational issues, such as unbounded length of streaming data, possibly very fast arrival rate, and just one scan over previously arrived click-sequences. In this paper, we propose a new, single-pass algorithm, called DSM-TKP (Data Stream Mining for Top-K Path traversal patterns), for mining top-k path traversal patterns, where k is the desired number of path traversal patterns to be mined. An effective summary data structure called TKP-forest (Top-K Path forest) is used to maintain the essential information about the top-k path traversal patterns of the click-stream so far. Experimental studies show that DSM-TKP algorithm uses stable memory usage and makes only one pass over the streaming data.en_US
dc.identifier.isbn0-7695-2415-Xen_US
dc.identifier.journal2005 IEEE/WIC/ACM International Conference on Web Intelligence, Proceedingsen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/18054
dc.identifier.wosnumberWOS:000234321300060
dc.language.isoen_USen_US
dc.titleDSM-TKP: Mining Top-K Path traversal patterns over Web click-streamsen_US
dc.typeProceedings Paperen_US

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