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    题名: DSM-PLW: Single-pass mining of path traversal patterns over streaming web click-sequences
    作者: 沈錳坤
    Li, Hua-Fu;Lee, Suh-Yin;Shan, Man-Kwan
    关键词: Web click-sequence streams;Path traversal patterns;Single-pass algorithm
    日期: 2006-06
    上传时间: 2009-08-24 12:29:32 (UTC+8)
    摘要: Mining Web click streams is an important data mining problem with broad applications. However, it is also a difficult problem since the streaming data possess some interesting characteristics, such as unknown or unbounded length, possibly a very fast arrival rate, inability to backtrack over previously arrived click-sequences, and a lack of system control over the order in which the data arrive. In this paper, we propose a projection-based, single-pass algorithm, called DSM-PLW (Data Stream Mining for Path traversal patterns in a Landmark Window), for online incremental mining of path traversal patterns over a continuous stream of maximal forward references generated at a rapid rate. According to the algorithm, each maximal forward reference of the stream is projected into a set of reference-suffix maximal forward references, and these reference-suffix maximal forward references are inserted into a new in-memory summary data structure, called SP-forest (Summary Path traversal pattern forest), which is an extended prefix tree-based data structure for storing essential information about frequent reference sequences of the stream so far. The set of all maximal reference sequences is determined from the SP-forest by a depth-first-search mechanism, called MRS-mining (Maximal Reference Sequence mining). Theoretical analysis and experimental studies show that the proposed algorithm has gently growing memory requirements and makes only one pass over the streaming data.
    關聯: Computer Networks, 50(10), 1474-487
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1016/j.comnet.2005.10.018
    DOI: 10.1016/j.comnet.2005.10.018
    显示于类别:[資訊科學系] 期刊論文

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