Efficient mining of fuzzy association rules from the pre-processed dataset

Computing and Informatics

Volumn 31, Issue 2, 2012, Pages 331-347

  Farzanyar, Zahra ^a   Kangavari, Mohammadreza ^a  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

Author keywords

Data mining; Domain ontology; Fuzzy association rule; Knowledge discovery; Linguistic terms

Indexed keywords

ASSOCIATION RULES; FUZZY RULES; LINGUISTICS; ONTOLOGY;

DATA MINING SYSTEM; DATA TUPLES; DOMAIN ONTOLOGIES; FUZZY ASSOCIATION RULE; FUZZY ASSOCIATIONS; HIGHLY-CORRELATED; LINGUISTIC TERMS; NOVEL TECHNIQUES;

DATA MINING;

EID: 84862554847     PISSN: 13359150     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (38)

1. CAI, Y.-CERCONE, N.-HAN, J.: Attribute-Oriented Induction in Relational Databases. In G. Piatetsky-Shapiro and W. J. Frawley (Eds.), Knowledge Discovery in Databases, AAAI/MIT Press 1991, pp. 213-228..
2. FAYYAD, U.-PIATETSKY-SHAPIRO, G.-SMYTH, P.: Knowledge Discovery and Data Mining: Towards a Unifying Framework. In KDD-96 Conference Proceedings, AAAI Press 1996..
3. HAN, J. W.-KAMBER, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco 2001..
4. AGRAWAL, R.-IMIELINSKI, T.-SWAMI, A.: Mining Association Rules Between Sets of Items in Large Databases. Proceedings of the ACM SIGMOD International Conference on Management of Data, May 1993, pp. 207-216..
5. SRIKANT, R.-AGRAWAL, R.: Mining Quantitative Association Rules in Large Relational Tables. Proc. of ACM-SIGMOD, Montreal, Canada 1996..
6. ZADEH, L. A.: Fuzzy Sets. Inform, and Control, Vol. 8, 1965, pp. 338-353..
7. HULLERMEIER, E.-BERINGER, J.: Mining Implication-Based Fuzzy Association Rules in Databases. In: B. Bouchon-Meunier, L. Foulloy, and R. R. Yager (Eds.): Intelligent Systems for Information Processing: From Representation to Applications, Elsevier 2003..
8. RUAN, D.-KERRE, E. E.: Fuzzy Implication Operators and Generalized Fuzzy Method of Cases. Fuzzy Sets and systems, Vol. 54, 1993, No. 1, pp. 23-38..
9. MILLER, R. J.-YANG, Y.: Association Rules over Interval Data. In: Proc. ACM SIGMOD Internat. Conf. Management of Data 1997, pp. 452-461..
10. th ACM Symp. on Applied Computing, San Jose, CA, Feb. 1997, pp. 88-90..
11. thACM Int'l Conf. on Information and Knowledge Management, Las Vegas, Nevada, Nov. 1997, pp. 209-215..
12. HONG, T. P.-Kuo, C. S.-CHI, S. C.: Mining Association Rules from Quantitative Data. Intell. Data Anal., Vol. 3, 1999, pp 363-376..
13. CHEN, G. Q.-WEI, Q.: Fuzzy Association Rules and the Extended Mining Algorithms. Information Sciences, Vol. 147, pp. 201-228..
14. CAI, C. H.-FU, W. O.-CHENG, C. H.-KWONG, W. W.: Mining Association Rules with Weighted Items. In: Proc. IDEAS 1998, pp. 68-77..
15. GYENESEI, A.: Mining Weighted Association Rules for Fuzzy Quantitative Items. TUCS Technical Report No: 346, May 2000..
16. YUE, S.-TSANG, E.-YEUNG, D.-SHI, D.: Mining Fuzzy Association Rules with Weighted Items. Proc. IEEE Internat. Conf. Systems Man Cybernet., 2000, pp. 1906-1911..
17. LEE, K. M.: Mining Generalized Fuzzy Quantitative Association Rules With Fuzzy Generalization Hierarchies. 0-7803-7078-3/01/10.00, 2001, IEEE..
18. Hu, Y. C.-CHEN, R. SH.-TZENG, G. H.: Discovering Fuzzy Association Rules Using Fuzzy Partition Methods. Knowledge-Based Systems, Vol. 16, 2003, pp. 137-147..
19. Au, W. H.-CHAN, K. C. C.: Mining Fuzzy Association Rules in a Bank-Account Database. IEEE Transactions on Fuzzy Systems, Vol. 11, 2003, No. 2..
20. GAO, Y.-MA, J.-MA, L.: A New Algorithm for Mining Fuzzy Association Rules. Proc. IEEE Internat. Conf. Machine Learning and Cybernetics 2004..
21. ISHIBUCHI, H.-NAKASHIMA, T.-YAMAMOTO, T.: Fuzzy Association Rules for Handling Continuous Attributes. In: Proc. IEEE ISIE 2001..
22. GYENESEI, A.: A Fuzzy Approach for Mining Quantitative Association Rules. TUCS Technical Report No: 336, March 2000..
23. ZHANG, W.: Mining Fuzzy Quantitative Association Rules. Proc. IEEE Internat. Conf. Tools Artif. Intell., 1999, pp. 99-102..
24. YAGER, R. R.: Fuzzy Summaries in Database Mining. Proc. Conf. Artif. Intell. Appl., 1995, pp. 265-269..
25. MILLS, F.: Statistical Methods. Pitman 1955..
26. Fu, A. W. C.-WONG, M. H.-SZE, S. C-WONG, W. C-WONG, W.L.Yu, W. K.: Finding Fuzzy Sets for the Mining of Association Rules for Numerical Attributes. In: Proc. IDEL, October 1998, pp. 263-268..
27. NG, R.-HAN, J.: Efficient and Effective Clustering Methods for Spatial Data Mining. In: Proc. Internat. Conf. Very Large Databases 1994..
28. HIROTA, K.-PEDRYCZ, W.: Linguistic Data Mining and Fuzzy Modelling. Proc. IEEE Internat. Conf. Fuzzy Systems, Vol. 2, 1996, pp. 1448-1496..
29. KAYA, M.-ALHAJJ, R.: Facilitating Fuzzy Association Rules Mining by Using Multi-Objective Genetic Algorithms for Automated Clustering. In: Proc. IEEE Internat. Conf. Data Mining, November 2003..
30. KAYA, M.-ALHAJJ, R.: Genetic Algorithm Based Framework for Mining Fuzzy Association Rules, Fuzzy Sets and Systems. Elsevier 2004..
31. ZADEH, L. A.: The Concept of a Linguistic Variable and Its Application to Approximate Reasoning. Information Science, Part 1. 1975..
32. CIVANLAR, M. R.-TRUSSELL, H. J.: Constructing Membership Functions Using Statistical Data. Fuzzy Sets and Systems, Vol. 18, 1986, pp. 1-14..
33. KOHONEN, R.: Self-Oganization and Associate Memory. Springer Verlag Berlin 1988..
34. GÓMEZ-PÉREZ, A.-FERNÁNDEZ-LÓPEZ, M.-CORCHO, O.: Ontological Engineering: With Examples from the Areas of Knowledge Management, E-commerce and the Semantic Web. Springer Verlag 2004..
35. DE NICOLA-MISSIKOFF, M.-NAVIGLI, R.: A Software Engineering Approach to Ontology Building. Information Systems, Vol. 34, 2009, pp. 258-275..
36. CORCHO, O.-FERNANDEZ, M.-GOMEZ-PEREZ: Methodologies, Tools and Languages for Building Ontologies: Where is the Meeting Point? Data and Knowledge Engineering 46, 2003..
37. http://www.anzdata.org.au/..
38. http : //www. nlm. nih. gov/research/umls/..