会议论文详细信息
2nd Annual International Conference on Information System and Artificial Intelligence | |
Link prediction in social network based on local information and attributes of nodes | |
物理学;计算机科学 | |
Liang, Yingying^1,2 ; Huang, Lan^1,2,3 ; Wang, Zhe^1,2 | |
College of Computer Science and Technology, Jilin University, Changchun | |
130012, China^1 | |
Key Laboratory of Symbolic Computation and Knowledge Engineering, Jilin University, Ministry of Education, Changchun | |
130012, China^2 | |
Zhuhai College of Jilin University, Zhuhai | |
519041, China^3 | |
关键词: Co-authorship networks; Feature vectors; Information sources; Link prediction; Local information; Topological information; | |
Others : https://iopscience.iop.org/article/10.1088/1742-6596/887/1/012043/pdf DOI : 10.1088/1742-6596/887/1/012043 |
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学科分类:计算机科学(综合) | |
来源: IOP | |
【 摘 要 】
Link prediction is essential to both research areas and practical applications. In order to make full use of information of the network, we proposed a new method to predict links in the social network. Firstly, we extracted topological information and attributes of nodes in the social network. Secondly, we integrated them into feature vectors. Finally, we used XGB classifier to predict links using feature vectors. Through expanding information source, experiments on a co-authorship network suggest that our method can improve the accuracy of link prediction significantly.
【 预 览 】
Files | Size | Format | View |
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Link prediction in social network based on local information and attributes of nodes | 194KB | download |