標題: DSM-TKP: Mining Top-K Path traversal patterns over Web click-streams
作者: Li, HF
Lee, SY
Shan, MK
資訊工程學系
Department of Computer Science
公開日期: 2005
摘要: 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.
URI: http://hdl.handle.net/11536/18054
ISBN: 0-7695-2415-X
期刊: 2005 IEEE/WIC/ACM International Conference on Web Intelligence, Proceedings
起始頁: 326
結束頁: 329
顯示於類別:會議論文