期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2021
卷号：21
期号：3
页码：275-286
DOI：10.22937/IJCSNS.2021.21.3.36
出版社：International Journal of Computer Science and Network Security
摘要：As a result of the vast amount of data that is geographically found in different locations. Distributed data mining (DDM) has taken a center stage in data mining. The use of mobile agents to enhance efficiency in DDM has gained the attention of industries, commerce and academia because it offers serious suggestions on how to solve inherent problems associated with DDM. In this paper, a novel DDM model has been proposed by using a mobile agent to enhance efficiency. The main idea behind the model is to use the Naive Bayes algorithm to give the mobile agent the ability to learn, compare, get and store the results on it from each server which has different datasets and we found that the accuracy increased roughly by 0.9% which is our main target.
