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Interesting patterns extraction using prior knowledge

Abstract : One important challenge in data mining is to extract interesting knowledge and useful information for expert users. Since data mining algorithms extracts a huge quantity of patterns it is therefore necessary to filter out those patterns using various measures. This paper presents IMAK, a part-way interestingness measure between objective and subjective measure, which evaluates patterns considering expert knowledge. Our main contribution is to improve interesting patterns extraction using relationships defined into an ontology.
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Contributor : Bibliothèque Télécom Bretagne <>
Submitted on : Tuesday, September 10, 2019 - 10:53:17 AM
Last modification on : Saturday, May 1, 2021 - 3:53:22 AM

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Laurent Brisson. Interesting patterns extraction using prior knowledge. Discovery science, Oct 2006, Barcelona, Spain. pp.296 - 300, ⟨10.1007/11893318_30⟩. ⟨hal-02282646⟩



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