MSGPs: A Novel Algorithm for Mining Sequential Generator Patterns
作者： Thi-Thiet Pham , Jiawei Luo , Tzung-Pei Hong , Bay Vo
DOI: 10.1007/978-3-642-34707-8_40
关键词:
摘要: Sequential generator pattern mining is an important task in data mining. patterns used together with closed sequential can provide additional information that alone are not able to provide. In this paper, we proposed algorithm called MSGPs, which based on the characteristics of and sequence extensions by doing depth-first search prefix tree, find all patterns. This uses a vertical approach listing counting support, prime block encoding factorization theory represent candidate sequences determine frequency for each candidate. Experimental results showed effective.
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