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Vers une mesure de similarité pour les séquences complexes

par Egho, Elias;Raïssi, Chedy;Calders, Toon ;Bourquard, Thomas;Jay, Nicolas;Napoli, Amedeo
Référence Revue des nouvelles technologies de l'information, E.24, page (335-340)
Publication Publié, 2013

Article révisé par les pairs

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Résumé :

Computing the similarity between sequences is a very important challenge for many different data mining tasks. There is a plethora of similarity measures for sequences in the literature, most of them being designed for sequences of items. In this work, we study the problem of measuring the similarity ratio between sequences of itemsets. We present new combinatorial results for efficiently counting distinct and common subsequences. These theoretical results are the cornerstone for an effective dynamic programming approach to deal with this problem.