Abstract
It is well known that local patterns are at the core of a lot of knowledge which may be discovered from data. Nevertheless, use of local patterns is limited by their huge number and computational costs. Several approaches (e.g., condensed representations, pattern set discovery) aim at selecting or grouping local patterns to provide a global view of the data. In this paper, we propose the idea of global constraints to write queries addressing global patterns as sets of local patterns. Usefulness of global constraints is to take into account relationships between local patterns, such relations expressing a user bias according to its expectation (e.g., search of exceptions, top-k patterns). We think that global constraints are a powerful way to get meaningful patterns. We propose the generic Approximate-and-Push approach to mine patterns under global constraints and we give a method for the case of the top-k patterns w.r.t. any measure. Experiments show its efficiency since it was not feasible to mine such patterns beforehand.
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References
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In: Advances in Knowledge Discovery and Data Mining, ch.12, AAAI/MIT Press (1996)
Bringmann, B., Zimmermann, A.: The chosen few: On identifying valuable patterns. In: Proceedings of the 12th IEEE International Conference on Data Mining (ICDM 2007), pp. 63–72 (2007)
Boulicaut, J.-F., Bykowski, A., Rigotti, C.: Free-sets: A condensed representation of boolean data for the approximation of frequency queries. Data Min. Knowl. Discov. 7(1), 5–22 (2003)
Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and regression trees. Statistics probability series. Wadsworth, Belmont (1984)
Calders, T., Rigotti, C., Boulicaut, J.-F.: A survey on condensed representations for frequent sets. In: Boulicaut, J.-F., De Raedt, L., Mannila, H. (eds.) Constraint-Based Mining and Inductive Databases. LNCS (LNAI), vol. 3848, pp. 64–80. Springer, Heidelberg (2006)
Crémilleux, B., Boulicaut, J.-F.: Simplest rules characterizing classes generated by delta-free sets. In: 22nd Int. Conf. on Knowledge Based Systems and Applied Artificial Intelligence (ES 2002), Cambridge, UK, December 2002, pp. 33–46. Springer, Heidelberg (2002)
De Raedt, L., Jäger, M., Lee, S.D., Mannila, H.: A theory of inductive query answering. In: Proceedings of the IEEE Conference on Data Mining (ICDM 2002), Maebashi, Japan, 2002, pp. 123–130 (2002)
De Raedt, L., Zimmermann, A.: Constraint-based pattern set mining. In: Proceedings of the Seventh SIAM International Conference on Data Mining, Minneapolis, Minnesota, USA, April 2007, SIAM, Philadelphia (2007)
Durand, N., Crémilleux, B.: ECCLAT: a New Approach of Clusters Discovery in Categorical Data. In: 22nd Int. Conf. on Knowledge Based Systems and Applied Artificial Intelligence (ES 2002), Cambridge, UK, December 2002, pp. 177–190. Springer, Heidelberg (2002)
Fu, A., R.W., Kwong, W., Tang, J.: Mining n-most interesting itemsets. In: Ohsuga, S., Raś, Z.W. (eds.) ISMIS 2000. LNCS (LNAI), vol. 1932, pp. 59–67. Springer, Heidelberg (2000)
Hand, D.J.: ESF exploratory workshop on Pattern Detection and Discovery in Data Mining. In: Pattern Detection and Discovery. LNCS, vol. 2447, pp. 1–12. Springer, Heidelberg (2002)
Knobbe, A., Ho, E.: Pattern teams. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) PKDD 2006. LNCS (LNAI), vol. 4213, pp. 577–584. Springer, Heidelberg (2006)
Liu, B., Hsu, W., Ma, Y.: Integrating classification and association rules mining. In: Proceedings of Fourth International Conference on Knowledge Discovery & Data Mining (KDD 1998), New York, August 1998, pp. 80–86. AAAI Press, Menlo Park (1998)
Mannila, H., Toivonen, H.: Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery 1(3), 241–258 (1997)
Morik, K., Boulicaut, J.-F., Siebes, A. (eds.): Local Pattern Detection. LNCS (LNAI), vol. 3539. Springer, Heidelberg (2005)
Ng, R.T., Lakshmanan, V.S., Han, J., Pang, A.: Exploratory mining and pruning optimizations of constrained associations rules. In: Proceedings of ACM SIGMOD 1998, pp. 13–24. ACM Press, New York (1998)
Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Discovering frequent closed itemsets for association rules. In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 398–416. Springer, Heidelberg (1998)
Pensa, R., Robardet, C., Boulicaut, J.-F.: A bi-clustering framework for categorical data. In: Jorge, A.M., Torgo, L., Brazdil, P.B., Camacho, R., Gama, J. (eds.) PKDD 2005. LNCS (LNAI), vol. 3721, pp. 643–650. Springer, Heidelberg (2005)
Siebes, A., Vreeken, J., van Leeuwen, M.: Item sets that compress. In: Proceedings of the Sixth SIAM International Conference on Data Mining, Bethesda, MD, USA, April 2006, SIAM, Philadelphia (2006)
Soulet, A., Crémilleux, B.: An efficient framework for mining flexible constraints. In: Ho, T.-B., Cheung, D., Liu, H. (eds.) PAKDD 2005. LNCS (LNAI), vol. 3518, pp. 661–671. Springer, Heidelberg (2005)
Soulet, A., Crémilleux, B.: Mining constraint-based patterns using automatic relaxation. Intelligent Data Analysis 13(1) (to appear). IOS Press
Suzuki, E.: Undirected discovery of interesting exception rules. International Journal of Pattern Recognition and Artificial Intelligence 16(8), 1065–1086 (2002)
Wang, K., Chu, X., Liu, B.: Clustering transactions using large items. In: Proceedings of ACM CIKM 1999 (1999)
Zimmermann, A., De Raedt, L.: Corclass: correlated association rule mining for classification. In: Suzuki, E., Arikawa, S. (eds.) DS 2004. LNCS (LNAI), vol. 3245, pp. 60–72. Springer, Heidelberg (2004)
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Crémilleux, B., Soulet, A. (2008). Discovering Knowledge from Local Patterns with Global Constraints. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69848-7_99
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DOI: https://doi.org/10.1007/978-3-540-69848-7_99
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