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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/39797

Title:	DSM-TKP: Mining Top-K Path Traversal Patterns over Web Click-Streams
Authors:	沈錳坤 Shan, Man-Kwan
Contributors:	國立政治大學資訊科學系
Keywords:	DSM-TKP;Mining;Top-K Path Traversal Patterns;Web Click-Streams
Date:	2005-09
Issue Date:	2010-05-27 16:50:43 (UTC+8)
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.
Relation:	2005 IEEE/WIC/ACM International Conference on Web Intelligence
Data Type:	conference
DOI link:	http://dx.doi.org/10.1109/WI.2005.56
DOI:	10.1109/WI.2005.56
Appears in Collections:	[Department of Computer Science ] Proceedings

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