On Dissimilarity Measures at the Fuzzy Partition Level

Grégory Smits 1 Olivier Pivert 1 Toan Duong
1 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : On the one hand, a user vocabulary is often used by soft-computing-based approaches to generate a linguistic and subjective description of numerical and categorical data. On the other hand, knowledge extraction strategies (as e.g. association rules discovery or clustering) may be applied to help the user understand the inner structure of the data. To apply knowledge extraction techniques on subjective and linguistic rewritings of the data, one first has to address the question of defining a dedicated distance metric. Many knowledge extraction techniques indeed rely on the use of a distance metric, whose properties have a strong impact on the relevance of the extracted knowledge. In this paper , we propose a measure that computes the dissimilarity between two items rewritten according to a user vocabulary.
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Communication dans un congrès
17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2018, Cadiz, Spain
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Soumis le : vendredi 23 mars 2018 - 15:03:15
Dernière modification le : mardi 24 avril 2018 - 13:38:01

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Grégory Smits, Olivier Pivert, Toan Duong. On Dissimilarity Measures at the Fuzzy Partition Level. 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2018, Cadiz, Spain. 〈hal-01741885〉

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