Measuring variation strength in gradual dependencies

New Dimensions in Fuzzy Logic and Related Technologies - Proceedings of the 5th EUSFLAT 2005 Conference

Volumn 1, Issue , 2007, Pages 337-344

  Molina, C ^a   Serrano, J M ^b   Sanchez, D ^b   Vila, M A ^b  

^a UNIVERSITY OF JAÉN   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY ASSOCIATION RULE; GRADUAL DEPENDENCIES;

ALGORITHMS; DATA MINING; FUZZY LOGIC; SEMANTICS;

FUZZY RULES;

EID: 70549100220     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proc. Of the 1993 ACM SIGMOD Conference, pages 207-216, 1993.
2. F. Berzal, I. Blanco, D. Sánchez, J.M. Serrano, and M.A. Vila. A definition for fuzzy approximate dependencies. Fuzzy Sets and Systems, 149(1):105-129, 2005.
3. F. Berzal, I. Blanco, D. Sánchez, and M.A. Vila. Measuring the accuracy and interest of association rules: A new framework. Intelligent Data Analysis, 6:221-235, 2002.
4. F. Berzal, J.C. Cubero, D. Sánchez, J.M. Serrano, and M.A. Vila. An alternative approach to discover gradual dependencies. Int. Journal of Uncertainty, Fuzziness and Knowledge-based Systems. Submitted.
5. S. Brin, R. Motwani, J.D. Ullman, and S. Tsur. Dynamic itemset counting and implication rules for market basket data. SIGMOD Record, 26(2):255-264, 1997. (Pubitemid 127456790)
6. M. Delgado, N. Marín, D. Sánchez, and M.A. Vila. Fuzzy association rules: General model and applications. IEEE Transactions on Fuzzy Systems, 11(2):214-225, 2003.
7. M. Delgado, D. Sánchez, and M.A. Vila. Fuzzy cardinality based evaluation of quantified sentences. International Journal of Approximate Reasoning, 23:23-66, 2000. (Pubitemid 34198918)
8. D. Dubois, E. Hüllermeier, and H. Prade. A systematic approach to the assessment of fuzzy association rules. Data Mining and Knowledge Discovery, 13(2):167-192, 2006. (Pubitemid 44352881)
9. M. Hahsler and K. Hornik. New probabilistic interest measures for association rules. Technical report, Department of Statistics and Mathematics, Vienna University of Economics and Business Administration, 2006.
10. E. Hüllermeier. Association rules for expressing gradual dependencies. In Proceedings PKDD 2002 Lecture Notes in Computer Science 2431, pages 200-211. 2002.
11. Chan-Man Kuok, Ada Fu, and Man Hon Wong. Mining fuzzy association rules in databases. SIGMOD Record, 27(1):41-46, 1998. (Pubitemid 128456025)
12. C. Silverstein, S. Brin, and R. Motwani. Beyond market baskets: Generalizing association rules to dependence rules. Data Mining and Knowledge Discovery, 2:39-68, 1998.
13. T. Sudkamp. Examples, counterexamples, and measuring fuzzy associations. Fuzzy Sets and Systems, 149(1):57-71, 2005.