Mining frequent disjunctive selection queries

Authors:
Inès Hilali-Jaghdam;Tao-Yuan Jen;Dominique Laurent;Sadok Ben Yahia
Affiliations:
ETIS - CNRS - ENSEA, University of Cergy Pontoise, France and Computer Sc. Dept, Faculty of Sciences of Tunis, Tunis, Tunisia;ETIS - CNRS - ENSEA, University of Cergy Pontoise, France;ETIS - CNRS - ENSEA, University of Cergy Pontoise, France;Computer Sc. Dept, Faculty of Sciences of Tunis, Tunis, Tunisia
Venue:
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Year:
2011

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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.