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Hierarchical Community Detection Algorithm Based on Node Similarity
| Content Provider | Semantic Scholar |
|---|---|
| Author | Xi, Jingke Zhan, Wenwei Wang, Zhixiao |
| Copyright Year | 2016 |
| Abstract | Louvain algorithm is a community detection algorithm based on modularity optimization. It is extremely fast, but the accuracy of detecting communities needs to be improved. This is because modularity of Louvain only considers link information between nodes and neglects the effect of the surrounding neighbor nodes, leading to decreased tightness between nodes in the same community and consequently affects accuracy. To solve this problem, by introducing node similarity to improve modularity function of Louvain algorithm, we propose a hierarchical community detection algorithm based on similarity (SHC).We adopt the Normalized Mutual Information to evaluate the accuracy of the algorithm and conduct experiments on the real network and the LFR synthetic network. The results show that the improved algorithm is more accurate, compared with Louvain and Newman Fast Algorithm. |
| Starting Page | 209 |
| Ending Page | 218 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| DOI | 10.14257/ijdta.2016.9.6.21 |
| Volume Number | 9 |
| Alternate Webpage(s) | http://www.sersc.org/journals/IJDTA/vol9_no6/21.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
