计算机与数字工程2024，Vol.52Issue(6)：1821-1829,9.DOI:10.3969/j.issn.1672-9722.2024.06.038
融合节点信息和社区信息的复杂网络链路预测
Research on Complex Network Link Prediction Combining Node Similarity and Community Information
孙博 1俞敏 1张冲1
作者信息
- 1. 华北电力大学控制与计算机工程学院 保定 071003
- 折叠
摘要
Abstract
As a challenging research direction in complex networks,link prediction has a very broad application prospect.Link prediction is called the prediction of missing or unobserved links in the network.The most cutting-edge link prediction meth-ods either only consider the similarity between nodes or simply mine the information between communities,and they don't achieve very good forecast purposes.In order to solve the above problems,this paper proposes a metric to measure the strength of the rela-tionship between overlapping communities and non-overlapping communities,and in order to better consider the impact of informa-tion between communities on predictions,a new community division method is also introduced,and finally a link prediction frame-work that considers node similarity and community structure information is proposed at the same time.Experimental results show that compared with the existing algorithms,the link prediction algorithm proposed in this paper improves the AUC accuracy by 0.2～10.59 percentage points,which proves that the method proposed in this paper is effective.关键词
复杂网络/链路预测/节点相似性/社区关系强度/社区划分Key words
complex network/link prediction/node similarity/strength of community relations/community division分类
信息技术与安全科学引用本文复制引用
孙博,俞敏,张冲..融合节点信息和社区信息的复杂网络链路预测[J].计算机与数字工程,2024,52(6):1821-1829,9.
