%A ZHU Peng-yu, BAO Pei-ming and JI Gen-lin %T Parallel Algorithm for Mining User Frequent Communication Relationship %0 Journal Article %D 2018 %J Computer Science %R 10.11896/j.issn.1002-137X.2018.02.018 %P 103-108 %V 45 %N 2 %U {https://www.jsjkx.com/CN/abstract/article_1132.shtml} %8 2018-02-15 %X With the rapid development of mobile communication technology and Internet,mobile communication equipment has become a portable tool for most people.A parallel algorithm PMFCS was proposed for mining frequent communication sub-graph of mass communication data.The algorithm is based on the Apriori algorithm and sub-graph connect principle.It uses Spark to distribute all the edges to each computing node,then the 1th-order frequent candidate sub-graphs are distributed to each node,the 1th-order frequent candidate sub-graphs are counted at each node,and the 1th-order sub-graphs are got by summarizing candidate sub-graphs.PMFCS iteratively connects the (k-1)th-order sub-graph and the 1th-order sub-graph to generate kth-order candidate sub-graphs.Subsequently,the algorithm terminates until the kth-order frequent sub-graph set is empty.The experimental results show that PMFCS can mine the frequent communication sub-graph efficiently and quickly.