Sequential Mining Method based on a New Criterion

S. Sakurai, Y. Kitahara, and R. Orihara (Japan)


Sequential Mining, Support, Confidence, Daily Business Report


Sequential mining methods efficiently discover all frequent sequential patterns using the Apriori property. However, analysts are not always interested in frequent patterns, be cause the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion which discovers interesting sequential pat terns for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is re lated to well-known criteria: the support and the confi dence. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Moreover, the paper shows its effect by applying it to daily business reports stored in a sales force automation system.

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