Discovering a cover set of ARsi with hierarchy from quantitative databases

Information Sciences

Volumn 173, Issue 4, 2005, Pages 319-336

  Yan, Peng ^a   Chen, Guoqing ^a  

^a Tsinghua University   (China)

Author keywords

Association rules; Fuzzy implication; Hierarchy; Rule cover set

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; DATABASE SYSTEMS; FUZZY SETS; HIERARCHICAL SYSTEMS; SEMANTICS;

ASSOCIATION RULES; FUZZY IMPLICATION; HIERARCHY; RULE COVER SET;

KNOWLEDGE BASED SYSTEMS;

EID: 19744365406     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2005.03.003     Document Type: Article

References (22)

1. R. Agrawal, T. Imielinski, A. Swami, Mining association rules between sets of items in large databases, in: Proc. of the ACM SIGMOD Conference on Management of Data, Washington, DC, 1993, pp. 207-216.
2. R. Agrawal, R. Srikant, Fast algorithms for mining association rules, in: Proceedings of VLDB Conference, Santiago, Chile, 1994. Expanded version available as IBM Research Report RJ9839.
3. W. Au, K. Chan, FARM: A data mining system for discovering fuzzy association rules, in Proceedings of 1999 IEEE International Fuzzy Systems Conference (Seoul, Korea).
4. C.H. Cai, A.W. Fu, C.H. Cheng, W.W. Kwong, Mining association rules with weighted items, in: Proceedings of 1998 Int. Database Engineering and Applications Symposium (IDEAS'98), Cardiff, Wales, UK, 1998, pp. 68-77.
5. G.Q. Chen Fuzzy Logic in Data Modeling: Semantics, Constraints and Database Design 1998 Academic Publishers Boston
6. G.Q. Chen, and Q. Wei Fuzzy association rules and the extended mining algorithms Information Sciences 147 2002 201 228
7. G.Q. Chen, Q. Wei, D. Liu, and G. Wets Simple association rules (SAR) and the SAR-based rule discovery Computer and Industrial Engineering 43 2002 721 733
8. G.Q. Chen, P. Yan, and E.E. Kerre Computationally efficient mining for fuzzy implication-based association rules in quantitative databases International Journal of General Systems 33 2-3 2004 163 182
9. J.M. Graff, W.A. Kosters, and J.J.W. Witteman Interesting fuzzy association rules in quantitative databases Lecture Notes in Computer Science 2168 2001 14 151
10. A. Gyenesei, A fuzzy approach for mining quantitative association rules, Turku Centre for Computer Science, TUCS Technical Reports, 2000, No. 336.
11. J. Han, and M. Kamber Data mining: Concepts and techniques 2000 Morgan Kaufmann Publishers
12. J. Han, Y. Fu, Discovery of multiple-level association rules from large databases, in: Proceedings of the 21st International Conference on Very Large Databases, Zurich, Switzerland, September, 1995.
13. J. Han, Y. Fu, Dynamic generation and refinement of concept hierarchies for knowledge discovery in databases, in: AAAr94 Workshop on Knowledge Discovery in Databases (KDD'94), Seattle, WA, 1994.
14. T.-P. Hong, C.-S. Kuo, and S.-C. Chi Trade-off between computation time and number of rules for fuzzy mining from quantitative data International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 9 5 2001 587 604
15. E. Hullermeier, Implication-based fuzzy association rules, in: ECML/PKDD 2001, Freiburg, Germany.
16. G.J. Klir, and B. Yuan Fuzzy sets and fuzzy logic theories and applications 1995 Prentice Hall PTR
17. J. Shu, E. Tsang, D.S. Yeung, D. Shi, Mining fuzzy association rules with weighted items, in: Proc. IEEE Int. Conf. on System, Man and Cybernetics (SMC2000), Nashville, Tennessee, 2000.
18. R. Srikant, R. Agrawal, Mining generalized association rules, in: Proceedings of the 21st VLDB Conference Zurich, Swizerland, 1995.
19. R. Srikant, R. Agrawal, Mining quantitative association rules in large relational tables, in: SIGMOD'96 6/96 Montreal, Canada, 1996.
20. P. Yan, G.Q. Chen, Mining non-redundant fuzzy quantitative association rules, in: Proceedings of International Conference on Fuzzy Information Processing Theories and Applications, Beijing, China, 2003.
21. P. Yan, G.Q. Chen, Properties and algorithmic improvement in discovering fuzzy implication-based association rules, in: Proceedings of Joint Conference on Information Sciences, 2003, pp. 131-134.
22. W. Zhang, Mining fuzzy quantitative association rules, in: Proceedings of 11th IEEE International Conference on Tools with Artificial Intelligence, Chicago, Illinois, 1999.