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Conference Papers Year : 2019

Fuzzy-Temporal Gradual Patterns

Abstract

Gradual patterns allow for retrieval of correlations between attributes through rules such as "the more the exercise, the less the stress". However, it may be the case that there is a lag between changes in some attributes and their impact on others ones, current methods do not take this into account. In this paper, we extend existing methods to handle these situations in order to retrieve patterns such as: "the more the exercise increases, the more the stress decreases 1 month later". We also extend our gradual rules to include fuzzy temporal constraints such as "the more the exercise increases, the more the stress decreases almost 1 month later". For this kinds of patterns, we designed three algorithms that were implemented and tested on real data.
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Dates and versions

lirmm-02085779 , version 1 (13-11-2019)

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Dickson Odhiambo Owuor, Anne Laurent, Joseph Onderi Orero. Fuzzy-Temporal Gradual Patterns. FUZZ-IEEE 2019 - International Conference on Fuzzy Systems, Jun 2019, New Orleans, LA, United States. pp.1-6, ⟨10.1109/FUZZ-IEEE.2019.8858883⟩. ⟨lirmm-02085779⟩
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