Mining Frequent Gradual Itemsets from Large Databases-Reference-Cited by-同舟云学术

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Mining Frequent Gradual Itemsets from Large Databases

Published:2009 Issue: Volume: Page:297-308
ISSN:0302-9743
Container-title:Advances in Intelligent Data Analysis VIII
language:
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Author:

Di-Jorio Lisa,Laurent Anne,Teisseire Maguelonne

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-03915-7_26

Reference12 articles.

1. Srikant, R., Agrawal, R.: Mining Quantitative Association Rules in Large Relational Tables. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pp. 1–12 (1996)

2. Lecture Notes in Artificial Intelligence;E. Hüllermeier,2002

3. Berzal, F., Cubero, J.C., Sanchez, D., Vila, M.A., Serrano, J.M.: An alternative approach to discover gradual dependencies. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) 15(5), 559–570 (2007)

4. Dubois, D., Prade, H.: Gradual elements in a fuzzy set. Soft Comput. 12(2), 165–175 (2008)

5. Galichet, S., Dubois, D., Prade, H.: Imprecise specification of ill-known functions using gradual rules. International Journal of Approximate Reasoning 35, 205–222 (2004)

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