计算机科学与探索2019，Vol.13Issue(3)：383-393,11.
加权好友推荐模型链路预测算法*
Link Prediction Algorithm of Weighted Friend Recommendation Model*
钱付兰 1杨强 2马闯 1张燕平2
作者信息
- 1. 安徽大学 计算机科学与技术学院,合肥 230601
- 2. 安徽大学 信息保障技术研究中心,合肥 230601
- 折叠
摘要
Abstract
As one of the important research directions of complex networks, it is a commonly used method based on node structure similarity to predict. There are lots of weak clique structures in real networks. The key problem of link prediction is to build algorithms for different network structures. Taking advantage of friends recommendation strategies in social networks, introducers tend to introduce their more familiar people to acceptors. This paper proposes a node similarity measure index which is more suitable for a particular type of weak clique structure because it combines local feature description and differentiates the difference between the influences of the user nodes effectively. The experimental results of the proposed friend recommendation model link prediction algorithm according to the index on 12 datasets show that the algorithm has obvious advantages on the two evaluation criteria of AUC and Precision.关键词
复杂网络/好友推荐/链路预测/相似性指标Key words
complex networks/ friend recommendation/ link prediction/ similarity index分类
信息技术与安全科学引用本文复制引用
钱付兰,杨强,马闯,张燕平..加权好友推荐模型链路预测算法*[J].计算机科学与探索,2019,13(3):383-393,11.
