Abstract
In this paper, we address the issue of mining frequent disjunctive selection queries in a given relational table. To do so, we introduce a level-wise algorithm to mine such queries whose selection condition is minimal. Then, based on these frequent minimal queries, and given any disjunctive selection query, we are able to decide whether its frequent or not. We carried out experiments on synthetic and real data sets that show encouraging results in terms of scalability.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Weiss, G.M., Zadrozny, B., Saar-Tsechansky, M.: Guest editorial: special issue on utility-based data mining. Data Mining and Knowledge Discovery 17(2), 129–135 (2008)
Nambiar, U.: Supporting Imprecision in Database Systems. In: Wang, J. (ed.) Encyclopedia of Data Warehousing and Mining, pp. 1884–1887 (2009)
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In: Advances in Knowledge Discovery and Data Mining, pp. 307–328 (1996)
Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Efficient mining of association rules using closed itemset lattices. Information Systems 24(1), 25–46 (1999)
Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., Lakhal, L.: Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets. In: Palamidessi, C., Moniz Pereira, L., Lloyd, J.W., Dahl, V., Furbach, U., Kerber, M., Lau, K.-K., Sagiv, Y., Stuckey, P.J. (eds.) CL 2000. LNCS (LNAI), vol. 1861, pp. 972–986. Springer, Heidelberg (2000)
Gouda, K., Zaki, M.J.: Efficiently mining maximal frequent itemsets. In: In IEEE International Conference on Data Mining, pp. 163–170. IEEE Computer Society, Los Alamitos (2001)
Jen, T.Y., Laurent, D., Spyratos, N.: Mining all frequent projection-selection queries from a relational table. In: Int. Conference on Extending Database Technology, pp. 368–379. ACM Press, New York (2008)
Jen, T.Y., Laurent, D., Spyratos, N.: Mining frequent conjunctive queries in star schemas. In: Int. Database Engineering Applications Symposium, pp. 97–108 (2009)
Goethals, B., Le Page, W., Mannila, H.: Mining association rules of simple conjunctive queries. In: Int. Conference SIAM-SDM, pp. 96–107 (2008)
Galambos, J., Simonelli, I.: Bonferroni-type Inequalities with Applications. Springer, Heidelberg (2000)
Hamrouni, T., Yahia, S.B., Nguifo, E.M.: Sweeping the disjunctive search space towards mining new exact concise representations for frequent itemsets. Data and Knowledge Engineering 68(10), 1091–1111 (2009)
Ullman, J.: Principles of Databases and Knowledge-Base Systems, vol. 1. Computer Science Press, Rockville (1988)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hilali-Jaghdam, I., Jen, TY., Laurent, D., Ben Yahia, S. (2011). Mining Frequent Disjunctive Selection Queries. In: Hameurlain, A., Liddle, S.W., Schewe, KD., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2011. Lecture Notes in Computer Science, vol 6861. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23091-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-23091-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23090-5
Online ISBN: 978-3-642-23091-2
eBook Packages: Computer ScienceComputer Science (R0)