关键词: 复杂网络, 好友推荐, 链路预测, 相似性指标

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.

Key words: complex networks, friend recommendation, link prediction, similarity index