Mining Negative and Positive Influence Rules Using Kullback-Leibler Divergence

Authors:
Leila Nemmiche Alachaher;Sylvie Guillaume
Affiliations:
Universite Blaise Pascal, France;Universite Blaise Pascal, France
Venue:
ICCGI '07 Proceedings of the International Multi-Conference on Computing in the Global Information Technology
Year:
2007

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Abstract

This paper describes a new method for mining negative and positive quantitative influence rules based on a coordination between a statistical dissimilarity measure (Kullback Leibler divergence) and contingency tables. This coordination identifies the significant positive and negative correlations and enables pertinent influence rules extraction.