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政大典藏 > College of Commerce > Department of Business Administation > Periodical Articles > Item 140.119/65454

Please use this identifier to cite or link to this item: https://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 link:	http://dx.doi.org/10.1177/0165551509103600
DOI:	10.1177/0165551509103600
Appears in Collections:	[Department of Business Administation] Periodical Articles

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