An efficient weighted graph aggregation algorithm

Graph aggregation (graph summarization) technique is one of the effective ways to mine and analyze huge graphs. However, in reality, these graphs are not only huge but also carry weighted edges. The current algorithms do not or seldom take the weight into consideration, leading to a great difference between the aggregation graph and the original one. In order to solve this problem and improve the quality and efficiency of graph aggregation, The weighted graph aggregation algorithm was studied, the consistency of grouping area values of the adjacent matrix of the aggregation graphs was introduced to measure the consistency of weights of edges, compression ratio was defined to measure the spatial efficiency of the graph aggregation algorithm, and error rate was used to evaluate the difference between the aggregation graph and the original graph. The compression quality is ensured by controlling error rates and a comparison is made between the proposed algorithm and the existing graph aggregation algorithms. The experiment results show the effectiveness of the graph aggregation algorithm.