%A Li Wenzheng,Gu Yijun,Yan Hongli %T Predicting Community Numbers with Network Bayesian Information Criterion %0 Journal Article %D 2020 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2019.0561 %P 72-82 %V 4 %N 4 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4817.shtml} %8 2020-04-25 %X

[Objective] This paper proposes an algorithm to predict the number of communities, aiming to improve the issues facing community detection algorithms. [Methods] First, we modified the Bayesian information criterion with characteristics of overlapping and non-overlapping community detection algorithms. Then, we constructed the Network Bayesian Information Criterion Algorithm to predict the number of communities. [Results] The accuracy and stability of the proposed algorithm were better than those of the Silhouette and Modularity algorithms. The accuracy of the former was 18% higher than those of the latter at least. [Limitations] Our new algorithm only includes the network structures. [Conclusions] The proposed algorithm based on Bayesian information criterion could effectively predict the number of network communities.