Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/39797
DC FieldValueLanguage
dc.contributor國立政治大學資訊科學系en_US
dc.creator沈錳坤zh_TW
dc.creatorShan, Man-Kwan-
dc.date2005-09en_US
dc.date.accessioned2010-05-27T08:50:43Z-
dc.date.available2010-05-27T08:50:43Z-
dc.date.issued2010-05-27T08:50:43Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/39797-
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.-
dc.languageen-USen_US
dc.language.isoen_US-
dc.relation2005 IEEE/WIC/ACM International Conference on Web Intelligenceen_US
dc.subjectDSM-TKP;Mining;Top-K Path Traversal Patterns;Web Click-Streamsen_US
dc.titleDSM-TKP: Mining Top-K Path Traversal Patterns over Web Click-Streamsen_US
dc.typeconferenceen
dc.identifier.doi10.1109/WI.2005.56en_US
dc.doi.urihttp://dx.doi.org/10.1109/WI.2005.56en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.languageiso639-1en_US-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeconference-
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