Evaluating interestingness measures with linear correlation graph

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

Volumn 4031 LNAI, Issue , 2006, Pages 312-321

  Huynh, Xuan Hiep ^a   Guillet, Fabrice ^a   Briand, Henri ^a  

^a UNIVERSITÉ DE NANTES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; DATA MINING; DATABASE SYSTEMS; LINEAR PROGRAMMING; MATHEMATICAL MODELS;

ASSOCIATION RULES; DATASETS; LINEAR CORRELATION GRAPH; PEARSON'S CORRELATION COEFFICIENT;

GRAPH THEORY;

EID: 33746191290     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11779568_35     Document Type: Conference Paper

References (18)

1. Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. Proceedings of 1993 ACM-SIGMOD International Conference on Management of Data. ACM Press, Washington DC, USA (1993) 207-216
2. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. VLDB'94, Proceedings of 20th International Conference on Very Large Data Bases. Morgan Kaufmann Publishers Inc., Santiago, Chile (1994) 487-499
3. Bayardo, Jr.R.J., Agrawal, R.: Mining the most interestingness rules. KDD'99, Proceedings of the 5th ACM SIGKDD International Confeference On Knowledge Discovery and Data Mining. ACM Press, San Diego, CA, USA (1999) 145-154
4. Blanchard, J., Guillet, F., Gras, R., Briand, H.: Assessing rule interestingness with a probabilistic measure of deviation from equilibrium. ASMDA'05, Proceedings of the 11th International Symposium on Applied Stochastic Models and Data Analysis. Brest, France (2005) 191-200
5. Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R.: Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, 1996.
6. Freitas, A.A.: On rule interestingness measures. Knowledge-Based Systems, 12(5-6). Elsevier, (1999) 309-315
7. Gavrilov, M., Anguelov, D., Indyk, P., Motwani, R.: Mining the stock market: which measure is best?. KDD'00, Proceedings of the 6th International Conference on Knowledge Discovery and Data Mining. Boston, MA, USA (2000) 487-496.
8. Hilderman, R.J., Hamilton, H.J.: Knowledge Discovery and Measures of Interestingness. Kluwer Academic Publishers (2001)
9. Huynh, X.H., Guillet, F., Briand, H.: ARQAT: an exploratory analysis tool for interestingness measures. ASMDA'05, Proceedings of the 11th International Symposium on Applied Stochastic Models and Data Analysis. Brest, France (2005) 334-344
10. Huynh, X.H., Guillet, F., Briand, H.: Clustering interestingness measures with positive correlation. ICEIS'05, Proceedings of the 7th International Conference on Enterprise Information Systems. Miami, USA (2005) 248-253
11. Kononenco, I.: On biases in estimating multi-valued attributes. IJCAI'95, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Montreal, Canada, (1995) 1034-1040
12. Liu, B., Hsu, W., Mun, L., Lee, H.: Finding interesting patterns using user expectations. IEEE Transactions on Knowledge and Data Mining 11(6). IEEE Educational Activities Department, (1999) 817-832
13. Newman, D.J., Hettich,S., Blake, C.L., Merz, C.J.: [UCI] Repository of machine learning databases, http://www.ics.uci.edu/~mlearn/MLRepository.html. University of California, Irvine, Department of Information and Computer Sciences, (1998).
14. Padmanabhan, B., Tuzhilin, A.: A belief-driven method for discovering unexpected patterns. KDD'98, Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining. ACM Press, New York, USA (1998) 94-100
15. Piatetsky-Shapiro, G.: Discovery, analysis and presentation of strong rules. Knowledge Discovery in Databases, G. Piatetsky-Shapiro and W. Frawley editors. MIT Press, Cambridge, MA (1991) 229-248
16. Ross, S.M.: Introduction to probability and statistics for engineers and scientists. Wiley, (1987)
17. Tan, P.N., Kumar, V., Srivastava, J.: Selecting the right objective measure for association analysis. Information Systems 29(4). Elsevier, (2004) 293-313
18. Vaillant, B., Lenca, P., Lallich, S.: A clustering of interestingness measures. DS'04, the 7th International Conference on Discovery Science, LNAI 3245. Springer-Verlag, Padova, Italy (2004) 290-297