Discovery of Unexpected Recurrence Behaviors in Sequence Databases - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Article Dans Une Revue International Journal of Computer Information Systems and Industrial Management Applications Année : 2010

Discovery of Unexpected Recurrence Behaviors in Sequence Databases

Haoyuan Li
Anne Laurent
Pascal Poncelet

Résumé

The discovery of unexpected behaviors in databases is an interesting problem for many real-world applications. In previous studies, unexpected behaviors are primarily addressed within the context of patterns, association rules, or sequences. In this paper, we study the unexpectedness with respect to the fuzzy recurrence behaviors contained in sequence databases. We first propose the notion of fuzzy recurrence rule, and then present the problem of mining unexpected sequences that contradict prior fuzzy recurrence rules. We also develop, UFR, an algorithm for discovering the sequences containing unexpected recurrence behaviors. The proposed approach is evaluated with Web access log data.
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Dates et versions

lirmm-00798703 , version 1 (02-04-2019)

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  • HAL Id : lirmm-00798703 , version 1

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Haoyuan Li, Anne Laurent, Pascal Poncelet. Discovery of Unexpected Recurrence Behaviors in Sequence Databases. International Journal of Computer Information Systems and Industrial Management Applications, 2010, 2, pp.279-288. ⟨lirmm-00798703⟩
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