Mining sequential patterns with itemset constraints
作者:Trang Van, Bay Vo, Bac Le
摘要
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.
论文关键词:Sequential pattern, Itemset constraint, Dynamic bit vector, Prefix-tree
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论文官网地址:https://doi.org/10.1007/s10115-018-1161-6