Mining Fuzzy-Temporal Gradual Patterns

Abstract

Gradual patterns allow for retrieval of the correlations between attributes through rules such as the more exercise, the less stress . However, it is possible that a temporal lag may exist between changes in some attributes and their impact on others, current methods do not take this into account. In this paper, we extend GRAANK approach using fuzzy temporal constraints to handle these situations and retrieve patterns such as: the more exercise, the less stress almost 1 month later . For this kind of patterns, we designed three algorithms that were implemented and tested on real data.