Hybrid Swarm Based Method for Link Prediction in Social Networks

Understanding the evolution of dynamic network structures is an emerging and very interesting topic, which is motivated by several real applications in many scientific fields. In this article, we discuss the link prediction problem, which is one of the key issues in the analysis of social evolving networks. We propose a new hybrid approach to predict the connections in social networks. The approach is inspired from the particle swarm algorithm and is combined with supervised machine learning strategy into a hybrid system. The paper includes an experimental study using real world data sets to compare the proposed methods against other approaches. The obtained results show good performance and prove the effectiveness of the proposed method.