Efficient serial episode mining with minimal occurrences

Authors:
Hideyuki Ohtani;Takuya Kida;Takeaki Uno;Hiroki Arimura
Affiliations:
Hokkaido University, Sapporo, Japan;Hokkaido University, Sapporo, Japan;National Institute of Informatics, Tokyo, Japan;Hokkaido University, Sapporo, Japan
Venue:
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Year:
2009

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Abstract

Recently, knowledge discovery in large data increases its importance in various fields. Especially, data mining from time-series data gains much attention. This paper studies the problem of finding frequent episodes appearing in a sequence of events. We propose an efficient depth-first search algorithm for mining frequent serial episodes in a given event sequence using the notion of right-minimal occurrences. Then, we present some techniques for speeding up the algorithm, namely, occurrence-deliver and tail-redundancy pruning. Finally, we ran experiments on real datasets to evaluate the usefulness of the proposed methods.