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Extraction incrémentale de séquences fréquentes dans un flux d'itemsets

Thomas Guyet 1, 2 René Quiniou 1
1 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
2 AGROCAMPUS OUEST
Abstract : We present a complete and correct incremental algorithm for mining frequent sequences in a sliding window over a stream of itemsets. It relies on a representation of frequent sequences inspired by the PSP algorithm and on an original method for counting the minimal occurrences of a sequence. Experiments made on simulated and real data show that our incremental algorithm significantly improves the computation time compared to a non-incremental approach.
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Conference papers
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https://hal.inria.fr/hal-00648893
Contributor : René Quiniou Connect in order to contact the contributor
Submitted on : Tuesday, December 6, 2011 - 3:29:58 PM
Last modification on : Saturday, October 9, 2021 - 3:57:07 AM

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  • HAL Id : hal-00648893, version 1

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CNRS | INRIA | UNIV-RENNES1 | IRISA | AGROCAMPUS-OUEST | UNAM | IRISA-D7 | UR1-MATH-STIC | UR1-UFR-ISTIC | AGROCAMPUS-OUEST-IRISA | UNIV-RENNES | INSTITUT-TELECOM | INSA-RENNES | EC-PARIS

Citation

Thomas Guyet, René Quiniou. Extraction incrémentale de séquences fréquentes dans un flux d'itemsets. Extraction et Gestion de Connaissances (EGC'2012), Jan 2012, Bordeaux, France. ⟨hal-00648893⟩

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