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| HAL : lirmm-00401364, version 1 |
| Fiche détaillée |  Récupérer au format |
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| International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems N/A (2009) 23 |
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| Discovering Fuzzy Unexpected Sequences with Concept Hierarchies |
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| Haoyuan Li 1, 2Anne Laurent 1 |
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| (2009) |
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| Sequential pattern mining is the method that has received much attention in sequence data mining research and applications, however, a drawback is that it does not profit from prior knowledge of domains. In our previous work, we proposed a belief-driven method with fuzzy set theory for discovering the unexpected sequences that contradict existing knowledge of data, including occurrence constraints and semantic contradictions. In this paper, we present a new approach that discovers unexpected sequences with determining semantic contradictions by using concept hierarchies associated with the data. We evaluate the effectiveness of our approach with experiments on Web usage analysis. |
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| 1 : | Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) |
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CNRS : UMR5506 – Université Montpellier II - Sciences et Techniques du Languedoc |
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| 2 : | Laboratoire de Génie Informatique et Ingénierie de Production (LGI2P) |
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Ecole des Mines d'Alès |
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| Domaine | : | Informatique/Base de données |
| lirmm-00401364, version 1 | |
| http://hal-lirmm.ccsd.cnrs.fr/lirmm-00401364 | |
| oai:hal-lirmm.ccsd.cnrs.fr:lirmm-00401364 | |
| Contributeur : Haoyuan Li | |
| Soumis le : Jeudi 2 Juillet 2009, 21:52:41 | |
| Dernière modification le : Vendredi 3 Juillet 2009, 10:06:11 | |
