- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Today, most large systems are overwhelmed by a flood of data that is stored daily in databases distributed. It is in this context that the distributed data mining is used by offering many parallel and distributed algorithms to extract crucial information. Among the most popular techniques, we are interested in our work at association rules technique by focusing on the distributed approach “the Count Distribution (CD)”. We aim for our contributions to improve this algorithm by reducing the number of exchanged messages, and the number of generated candidates. Our algorithm is based on the sequential algorithm AClose of the closed frequents itemsets approch. The experimental results showed that the proposed algorithm meets the expected objectives by presenting a performance gain greater than the CD algorithm in which the last points are important performance factors in determining the quality of an algorithm for extraction rules.