Disjunctive sequential patterns on single data sequence and its anti-monotonicity

Authors:
Kazuhiro Shimizu;Takao Miura
Affiliations:
Dept.of Elect.& Elect. Engr., HOSEI University, Tokyo, Japan;Dept.of Elect.& Elect. Engr., HOSEI University, Tokyo, Japan
Venue:
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2005

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Abstract

In this work, we proposes a novel method for mining frequent disjunctive patterns on single data sequence. For this purpose, we introduce a sophisticated measure that satisfies anti-monotonicity, by which we can discuss efficient mining algorithm based on APRIORI. We discuss some experimental results.