Mining sequential patterns with itemset constraints |
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Authors: | Trang Van Bay Vo Bac Le |
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Affiliation: | 1.Faculty of Information Technology,Ho Chi Minh City University of Technology,Ho Chi Minh City,Vietnam;2.Faculty of Computer Science,VNUHCM, University of Information Technology,Ho Chi Minh City,Vietnam;3.Faculty of Information Technology,VNUHCM, University of Science,Ho Chi Minh City,Vietnam |
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Abstract: | Mining sequential patterns is used to discover all the frequent sequences in a sequence database. However, the mining may return a huge number of patterns, while the users are only interested in a particular subset of these. In this paper, we consider the problem of mining sequential patterns with itemset constraints. In order to solve this problem, we propose a new algorithm named MSPIC-DBV, which is a pattern-growth algorithm that uses prefixes and dynamic bit vectors. This algorithm prunes the search space at the beginning and during the mining process. Moreover, it reduces the number of candidates that need to be checked. The experimental results show that the proposed algorithm outperforms the previous methods. |
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