Interestingness of discovered association rules in terms of neighborhood-based unexpectedness

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1394, Issue , 1998, Pages 72-86

  Dong, Guozhu ^a   Li, Jinyan ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES;

ACTIONABILITY; CENTRAL PROBLEMS; INTERESTING RULES; INTERESTINGNESS; SUPPORT AND CONFIDENCE; USER NEED;

DATA MINING;

EID: 84958986420     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-64383-4_7     Document Type: Conference Paper

References (13)

1. R. Agrawal, T. Imielinski, and A. Swami. Data mining: a performance perspective. IEEE Transactions on Knowledge and Data Engineering, 5(6): 914-925, 1993.
2. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pages 207-216, Washington, D. C., 1993.
3. M.-S. Chen, J. Han, and P S. Yu. Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, 8(6): 866-882, 1996.
4. Y. Fu and J. Han. Meta-rule-guided mining of association rules in relational databases. Proc. 1995 Int’l Workshop, on Knowledge Discovery and Deductive and Object-Oriented Databases (KDOOD’95), Singapore, December 1995, pp. 39-46.
5. M. Klemettinen, H. Mannila, P. Ronkainen, H. Toivonen, and A. I. Verkamo. Finding interesting rules from large sets of discovered association rules. In Proceedings of the Third International Conference on Information and Knowledge Management, pages 401-407, Gaithersburg, Maryland, 1994.
6. B. Liu and W. Hsu. Post-analysis of learned rules. In Proceedings of AAAI, pages 828-834, 1996.
7. G. Piatetsky-Shapiro. Discovery, analysis, and presentation of strong rules. In Knowledge Discovery in Databases, G. Piatetsky-Shapiro and W. J. Frawleay, Eds, pages 229-248. AAAI Press/The MIT Press, Menlo Park, CA, 1991.
8. G. Piatetsky-Shapiro and C. J. Matheus. The interestingness of deviations. In Proceedings of the AAAI-94 Workshop on Knowledge Discovery in Databases, pages 25-36, 1994.
9. R. Srikant and R. Agrawal. Mining generalized association rules. IBM Research Report RJ 9963, 1996.
10. A. Silberschatz and A. Tuzhilin. On subjective measures of interestingness in knowledge discovery. In Proceedings of the First International Conference on Knowledge Discovery and Data Mining, pages 275-281, Montreal, Canada, August, 1995
11. A. Silberschatz and A. Tuzhilin. What makes patterns interesting in Knowledge discovery systems. IEEE Transactions on Knowledge and Data Engineering, 8(6):970-974, December, 1996.
12. H. Toivonen, M. Klemettinen, P. Ronkainen, K. Hätönen and H. Mannila. Pruning and grouping discovered association rules. In MLnet Workshop on Statistics, Machine Learning, and Discovery in Databases, Crete, Greece, April 1995.
13. A. Tuzhilin. A pattern discovery algebra. In Proceedings of the 1997 Workshop on Research Issues in Data Mining and Knowledge Discovery, 1997.