Social network link prediction method based on subgraph evolution and improved ant colony optimization algorithm
Based on improved ant colony algorithm and subgraph evolution fusion, a new unsupervised social network link prediction method (SE-ACO) was proposed.First, the special subgraph was determined in the social network graph.Then the evolution of the subgraph was studied to predict the new links in the g...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2020-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436X.2020223/ |
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| Summary: | Based on improved ant colony algorithm and subgraph evolution fusion, a new unsupervised social network link prediction method (SE-ACO) was proposed.First, the special subgraph was determined in the social network graph.Then the evolution of the subgraph was studied to predict the new links in the graph, and the special subgraph was located by the ant colony method.Finally, using different network topology environments and data sets to test the proposed method.Compared with other unsupervised social network prediction algorithms, the proposed SE-ACO method has the best evaluation results, shorter running time and the best effect on most data sets, which indicates that graph structure plays an important role in link prediction algorithm. |
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| ISSN: | 1000-436X |