Contrast set mining in temporal databases

Abstract

Understanding the underlying differences between groups or classes in certain contexts can be of the utmost importance. Contrast set mining relies on discovering significant patterns by contrasting two or more groups. A contrast set is a conjunction of attribute–value pairs that differ meaningfully in its distribution across groups. A previously proposed technique is rules for contrast sets, which seeks to express each contrast set found in terms of rules. This work extends rules for contrast sets to a temporal data mining task. We define a set of temporal patterns in order to capture the significant changes in the contrasts discovered along the considered time line. To evaluate the proposal accuracy and ability to discover relevant information, two different real-life data sets were studied using this approach.