完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Li, HF | en_US |
dc.contributor.author | Lee, SY | en_US |
dc.contributor.author | Shan, MK | en_US |
dc.date.accessioned | 2014-12-08T15:25:38Z | - |
dc.date.available | 2014-12-08T15:25:38Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 0-7695-2415-X | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/18054 | - |
dc.description.abstract | Online, 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.language.iso | en_US | en_US |
dc.title | DSM-TKP: Mining Top-K Path traversal patterns over Web click-streams | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2005 IEEE/WIC/ACM International Conference on Web Intelligence, Proceedings | en_US |
dc.citation.spage | 326 | en_US |
dc.citation.epage | 329 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000234321300060 | - |
顯示於類別: | 會議論文 |