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題名: | DSM-PLW: Single-pass mining of path traversal patterns over streaming web click-sequences | 作者: | 沈錳坤 Li, Hua-Fu ; \r\nLee, Suh-Yin ; \r\nShan, Man-Kwan |
關鍵詞: | Web click-sequence streams; \r\nPath traversal patterns; \r\nSingle-pass algorithm | 日期: | Jun-2006 | 上傳時間: | 24-Aug-2009 | 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 | 資料類型: | article | DOI: | http://dx.doi.org/10.1016/j.comnet.2005.10.018 |
Appears in Collections: | 期刊論文 |
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