A Big Graph Clustering Algorithm Based on MapReduce

Abstract

Graph clustering is an important technology in graph analysis area, the measure of similarity between node of graph is the presise for graph clustering. SimRank algorithm is a kind of universal structure similarity calculation model which is proposed by Jeh and Widom. SimRank algorithm using iterative method to calculate the similarity between nodes, so the time and space complexity is very high. With the rapid increase of data, the ability of single machine can not meet the requirement of the large-scale data calculation. In this paper, the distributed SimRank algorithm was proposed based on Mapreduce and was used to measure the similarity of graph. Then the distributed AP clustering algorithm was designed for clustering analysis graph nodes. The experimental was executed to compare the clustering running time and speedup and results show that the method can efficiently complete graph nodes similarity measure and clustering the large graph effectively.