Extraction of Association Rules from Data Stream Using Genetic Algorithm

In this work, we are interested in the extraction of association rules on the data stream. We propose three strategies to deal with this problem: resolution by local vision, resolution by local and independent global vision, resolution by global vision. Since this task is very time consuming, the genetic algorithm for extraction of association rules GAARM is used to speed up the extraction process. The strategies have been tested on two datasets of different size and have given promising results.