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Proceedings Paper

Algorithm based on time-window for mining sequential patterns in relational database
Author(s): Zhenyu Wang; Lifeng Bian; Xiaoshu Hang
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Paper Abstract

Mining sequential patterns is an important topic in the data mining (DM) or knowledge discovery in database (KDD) research. At present, its research and application are mainly focused on analyzing transaction data of market. As the transaction database is very different from general relational database at the aspect of inner makeup, this paper makes relevant study and discussion on how to mine sequential patterns from general relational database. In this paper, a strategy based on time-window is adopted instead of general Apriori algorithm. At last, an algorithm based on time-window for mining sequential patterns (TW_SP) is put forward, and its correctness and validity is further proved by the experiment in a real relational database.

Paper Details

Date Published: 18 September 2001
PDF: 6 pages
Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); doi: 10.1117/12.440302
Show Author Affiliations
Zhenyu Wang, Hefei Institute of Intelligent Machines (China)
Lifeng Bian, Hefei Institute of Intelligent Machines (China)
Xiaoshu Hang, Univ. of Science and Technology of China (China)

Published in SPIE Proceedings Vol. 4556:
Data Mining and Applications
Deren Li; Jie Yang; Jufu Feng; Shen Wei, Editor(s)

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