標題: Mining Top-K Path Traversal Patterns over Streaming Web Click-Sequences
作者: Li, Hua-Fu
Lee, Suh-Yin
資訊工程學系
Department of Computer Science
關鍵字: web usage mining;data streams;path traversal patterns;top-k pattern mining;single-pass mining
公開日期: 1-Jul-2009
摘要: Online, one-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 Web 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 a set of 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 (a forest of Top-K Path traversal patterns), is used to maintain the essential information about the top-k path traversal patterns generated so far. Experimental studies show that the proposed DSM-TKP algorithm uses stable memory usage and makes only one pass over the streaming Web click-sequences.
URI: http://hdl.handle.net/11536/7083
ISSN: 1016-2364
期刊: JOURNAL OF INFORMATION SCIENCE AND ENGINEERING
Volume: 25
Issue: 4
起始頁: 1121
結束頁: 1133
Appears in Collections:Conferences Paper


Files in This Item:

  1. 000268197700010.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.