Hafida Belbachir

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—Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a(More)
Dans les sciences de l'information géographique les champs continus sont utilisés pour modéliser et représenter des phénomènes continus naturels et environnementaux. Ils sont d'un grand intérêt pour décrire la distribution de plusieurs propriétés physiques qui varient continuellement dans l'espace et dans le temps, comme la météorologie. Notre article(More)
The parallel and distributed systems represent one of the important solutions proposed to ameliorate the performance of the sequential association rule mining algorithms. However, parallelization and distribution process is not trivial and still facing many problems of synchronization, communication, and workload balancing. Our study is limited to the(More)
Apriori Algorithms are used on very large data sets with high dimensionality. Therefore parallel computing can be applied for mining of association rules. The process of association rule mining consists of finding frequent item sets and generating rules from the frequent item sets. Finding frequent itemsets is more expensive in terms of CPU power and(More)
Data mining has become an important technology to discover a hidden and nontrivial knowledge from large amounts of data. A major problem is to achieve this discovery process with preserving privacy of extracted data and / or knowledge. Privacy preserving data mining (PPDM) is a new area of research that studies the side effects of knowledge mining methods(More)