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    政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 >  Item 140.119/65454
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/65454


    Title: Mining Sequential Patterns in Business-to-business(B2B) Environment
    Authors: 唐揆
    Hu, Ya-Han;Chen, Yen-Liang;Tang, Kwei
    Contributors: 企管系
    Keywords: business-to-business;data mining;sequential pattern
    Date: 2009.12
    Issue Date: 2014-04-17 12:39:09 (UTC+8)
    Abstract: Sequential pattern mining is a powerful data mining technique for finding time-related behaviour in sequence databases. In this paper, we focus on mining sequential patterns in the business-to-business (B2B) environment. Because customers’ sequences in the B2B environment are very long, and almost all items are frequently purchased by all customers, using traditional methods may result in a large number of uninteresting and meaningless patterns and a long computational time. To solve these problems, we introduce three conditions (constraints) — compactness, repetition, and recency — and consider them jointly with frequency in selecting sequential patterns. An efficient algorithm is developed to discover frequent sequential patterns which satisfy the conditions. Empirical results show that the proposed method is computationally efficient and effective in extracting useful sequential patterns in the B2B environment.
    Relation: Journal of Information Science,35(6),677-694
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1177/0165551509103600
    DOI: 10.1177/0165551509103600
    Appears in Collections:[企業管理學系] 期刊論文

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