Applying cluster-based fuzzy association rules mining framework into EC environment

Applied Soft Computing Journal

Volumn 12, Issue 8, 2012, Pages 2114-2122

  Chiu, Hung Pin ^a   Tang, Yi Tsung ^b   Hsieh, Kun Lin ^c  

^a NANHUA UNIVERSITY   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^c NATIONAL TAITUNG UNIVERSITY   (Taiwan)

Author keywords

Clustering based data mining; Electronic commerce (EC); Fuzzy association rule; Fuzzy membership functions

Indexed keywords

CLUSTER-BASED; CONFIDENCE VALUES; FUZZY ASSOCIATION RULE; FUZZY MEMBERSHIP FUNCTION; INFORMATION DATABASE; ITEM SETS; MARKETING STRATEGY; MINING ARCHITECTURE; MINING ASSOCIATIONS; RULE MINING; TRANSACTION DATABASE; TRANSACTION INFORMATION; WEB USAGE;

ASSOCIATION RULES; CLUSTER COMPUTING; DATA MINING; DATABASE SYSTEMS; ELECTRONIC COMMERCE;

FUZZY RULES;

EID: 84861865521     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.08.010     Document Type: Article

References (29)

1. A. Kandel Fuzzy Expert Systems 1992 CRC Press Boca Raton, FL pp. 8-19
2. C.C. Chang, Y.C. Li, and J.S. Lee An efficient algorithm for incremental mining of association rules Proceedings of 2005 RIDE-SDMA IEEE International Workshop on Research Issues in Data Engineering: Stream Data Mining and Application 2005 3 10
3. D. Arotaritei, and S. Mitra Web mining: a survey in the fuzzy framework Fuzzy Sets and Systems 2004 5 19
4. D. Yu, Q. Hu, and C. Wu Uncertainty measures for fuzzy relations and their applications Applied Soft Computing 7 3 2007 1135 1143 (Pubitemid 46551939)
5. H. Ishibuchi, K. Nozaki, and H. Tanaka Distributed representation of fuzzy rules and its application to pattern classification Journal of Fuzzy Sets and Systems 52 1 1992 21 32
6. H. Ishibuchi, K. Nozaki, N. Yamamoto, and H. Tanaka Selecting fuzzy if-then rules for classification problems using genetic algorithms IEEE Transaction on Fuzzy Systems 3 3 1995 260 270
7. H. Toivonen Sampling large database for association rule VLDB 1996 134 145
8. J. Han, and M. Kamber Data Mining: Concepts and Techniques 2000 Morgan Kaufmann Los Altos
9. J. Han, and Y. Fu Discovery of multiple-level association rules from large database The International Conference on Very Large Databases 1995 420 431
10. J.S. Park, M.S. Chen, and P.S. Yu An effective hash based algorithm for mining association rules Proceedings of ACM SIGMOD 1995 175 186
11. L.A. Zadeh Fuzzy sets Information and Control 1965 338 353
12. M.S. Chen, J. Han, and P.S. Yu Data mining: an overview from a database perspective IEEE Transactions on Knowledge and Data Engineering 1996 866 883 (Pubitemid 126774144)
13. P. Cabena, P. Hadjinian, R. Stadler, J. Verhees, and A. Zanasi Discovering Data Mining from Concept to Implementation 1997 Englewood Cliffs Prentice-Hall
14. P.S.M. Tsai, and C.M. Chen Mining interesting association rules from customer databases and transaction databases Information Systems 2004 685 696
15. R. Agrawal, T. Imielinksi, and A. Swami Mining association rules between sets of items in large database The 1993 ACM SIGMOD Conference Washington, DC, USA 1993 1 10
16. R. Agrawal, T. Imielinksi, and A. Swami Database mining: a performance perspective IEEE Transactions on Knowledge Data Engineering 1993 914 925
17. R. Agrawal, and R. Srikant Fast algorithm for mining association rules in large databases Proceedings of 1994 International Conference on VLDB 1994 487 499
18. R. Agrawal, and R. Srikant Mining generalized association rules The International Conference on Very Large Databases 1995 407 419
19. R. Agrawal, and R. Srikant Mining quantitative association rules in large relational tables The 1996 ACM SIGMOD International Conference on Management of Data Monreal, Canada June 1996 1 12 (Pubitemid 126440751)
20. R. Cooley, B. Mobasher, and J. Srivastava Web mining: information and pattern discovery on the world wide web Proceedings of the 9th IEEE International Conference on Tools with Artificial Intelligence (ICYAI'97) November 1997 558 567
21. S.R. Kumar, K. Dinesh, and K. Pradeep Predicting uncertain behavior of industrial system using FM - a practical case Applied Soft Computing 8 1 2008 96 109
22. S. Brin, R. Motwani, J.D. Ullman, and S. Tsur Dynamic itemset counting and implication rules for marketing basket data 1997 ACM SIGMOD Conference on Management of Data 1997 255 264 (Pubitemid 127456790)
23. S.L. Wang, and A. Jafari Hiding sensitive predictive association rules 2005 IEEE International Conference on Systems, Man and Cybernetics 2005 164 169 (Pubitemid 41674875)
24. T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama Mining optimized association rules for numeric attributes The ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems 1996 182 191
25. T.F. Liang Interactive multi-objective transportation planning decisions using fuzzy linear programming Asia Pacific Journal of Operational Research 25 1 2008 11 31
26. T.P. Hong, C.S. Kuo, and S.C. Chi A data mining algorithm for transaction data with quantitative values Intelligence Data Analysis 1999 363 376 (Pubitemid 33260723)
27. T.P. Hong, C.S. Kuo, and S.C. Chi Mining association rules from quantitative data Intelligence Data Analysis 1999 363 376 (Pubitemid 33260723)
28. T.P. Hong, K.Y. Lin, and S.L. Wang Fuzzy data mining for interesting generalized association rules Fuzzy Sets and Systems 2003 255 269
29. Y.-J. Tsay, and J.-Y. Chiang CBAR: an efficient method for mining association rules Knowledge-Based Systems 2005 99 105 (Pubitemid 40402982)