Application of Link Prediction in Temporal Networks
Link prediction is an important research hotspot in complex networks.Correlational studies merely use static topology for prediction,without considering the influence of network dynmie evolutionary process on link prediction.We believe that the links are derived from the evolutionary process of network,and dynamic network topology will contain more information,Moreover,many networks have time attribute naturally,which is apt to combine the similarity of time and structure for link prediction.The paper proposes the concept of active factor using time attribute,to extend the similarity based rink prediction framework.Then model and analysis the data of citation network and cooperation network with temporal networks.Design the active factors for both network sand verify the performance of these new indexes.The results shows that the indexes with active factor perform better than structure similarity based indexes.
active factor complex networks link prediction temperal networks
Haihang Xu Lijun Zhang
Department of Computer Science, Beijing University of Aeronautics and Astronautics, Beijing, 100191, China
国际会议
太原
英文
241-244
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）