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    題名: DSM-TKP: Mining Top-K Path Traversal Patterns over Web Click-Streams
    作者: 沈錳坤
    Shan, Man-Kwan
    貢獻者: 國立政治大學資訊科學系
    關鍵詞: DSM-TKP;Mining;Top-K Path Traversal Patterns;Web Click-Streams
    日期: 2005-09
    上傳時間: 2010-05-27 16:50:43 (UTC+8)
    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.
    關聯: 2005 IEEE/WIC/ACM International Conference on Web Intelligence
    資料類型: conference
    DOI 連結: http://dx.doi.org/10.1109/WI.2005.56
    DOI: 10.1109/WI.2005.56
    顯示於類別:[資訊科學系] 會議論文

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