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User-driven Association Rule Mining Using a Local Algorithm

Abstract : One of the main issues in the process of Knowledge Discovery in Databases is the Mining of Association Rules. Although a great variety of pattern mining algorithms have been designed to this purpose, their main problems rely on in the large number of extracted rules, that need to be filtered in a post-processing step resulting in fewer but more interesting results. In this paper we suggest a new algorithm, that allows the user to explore the rules space locally and incrementally. The user interests and preferences are represented by means of the new proposed formalism - the Rule Schemas. The method has been successfully tested on the database provided by Nantes Habitat.
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Contributor : Claudia Marinica <>
Submitted on : Friday, October 16, 2009 - 2:51:46 PM
Last modification on : Monday, July 1, 2019 - 12:02:19 PM

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Claudia Marinica, Andrei Olaru, Fabrice Guillet. User-driven Association Rule Mining Using a Local Algorithm. 11th International Conference on Enterprise Information Systems, May 2009, Milan, Italy. pp.200-205, ⟨10.5220/0002003002000205⟩. ⟨hal-00424596⟩



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