参考文献
[1]HOLME P,SARAMKI J.Temporal Networks[J].Physics Reports,2012,519(3):97-125.
[2]ZHANG Jun,WANG Chaokun,WANG Jianmin,et al.Inferring Continuous Dynamic Social Influence and Personal Preference for Temporal Behavior Prediction[J].Proceedings of VLDB Endowment,2014,8(3):269-280.
[3]GOMEZ R M,LESKOVEC J,KRAUSE A.Inferring Networks of Diffusion and Influence[J].ACM Transac-tions on Knowledge Discovery from Data,2010,5(4):1019-1028.
[4]ABRAHAO B,CHIERICHETTI F,KLEINBERG R,et al.Trace Complexity of Network Inference[C]//Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,USA:ACM Press,2013:491-499.
[5]GOMEZ R M,BALDUZZI D,SCHLKOPF B,et al.Uncovering the Temporal Dynamics of Diffusion Networks[C]//Proceedings of the 28th International Conference on Machine Learning.[S.l.]:International Machine Learning Society,2011:561-568.
[6]RONG Yu,ZHU Qiankun,CHENG Hong.A Model-free Approach to Infer the Diffusion Network from Event Cascade[C]//Proceedings of the 25th ACM Inter-national on Conference on Information and Knowledge Management.New York,USA:ACM Press,2016:1653-1662.
[7]LESKOVEC J,FALOUTSOS C.Sampling from Large Graphs[C]//Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,USA:ACM Press,2006:631-636.
[8]MEHDIABADI M E,RABIEE H R,SALEHI M.Sampling from Diffusion Networks[C]//Proceedings of International Conference on Social Informatics.[S.l.]:AAAI,2012:106-112.
[9]CHEN Wei,WANG Chi,WANG Yajun.Scalable Influence Maximization for Prevalent Viral Marketing in Large-scale Social Networks[C]//Proceedings of Inter-national Conference on Social Informatics.New York,USA:ACM Press,2010:1029-1038.
[10]XIE Miao,YANG Qiusong,WANG Qing,et al.DynaDiffuse:A Dynamic Diffusion Model for Continuous Time Constrained Influence Maximization[C]//Pro-ceedings of the 29th AAAI Conference on Artificial Intelligence.[S.l.]:AAAI,2015:346-352.
[11]DU Nan,LIANG Yingyu,Balcan M F,et al.Influence Function Learning in Information Diffusion Networks[C]//Proceedings of International Conference on Machine Learning.Beijing,China:[s.n.],2014:2016-2024.
[12]RODRIGUEZ M G,SCHLKOPF B.Influence Maximization in Continuous Time Diffusion Networks[J].Cement and Concrete Composites,2012,34(5):684-691.
[13]NAJAR A,DENOYER L,GALLINARI P.Predicting Information Diffusion on Social Networks with Partial Knowledge[C]//Proceedings of the 21st International Conference Companion on World Wide Web.Lyon,France:[s.n.],2012:1197-1204.
(上接第39页)
[14]GUILLE A.Information Diffusion in Online Social Networks[C]//Proceedings of SIGMOD/PODS’13.New York,USA:[s.n.],2013:31-36.
[15]KEMPE D,KLEINBERG J,TARDOS .Maximizing the Spread of Influence Through a Social Network[C]//Proceedings of the 9th ACM SIGKDD.New York,USA:ACM Press,2003:137-146.
[16]IWATA T,SHAH A,GHAHRAMANI Z.Discovering Latent Influence in Online Social Activities via Shared Cascade Poisson Processes[C]//Proceedings of SIGKDD’13.New York,USA:ACM Press,2013:266-274.
[17]GOMEZ R M,LESKOVEC J,SCHLKOPF B.Structure and Dynamics of Information Pathways in Online Media[C]//Proceedings of ACM WSDM Conference.New York,USA:ACM Press,2012:23-32.
[18]曹玉林,马建萍.基于微分方程的移动自组网病毒传播模型研究[J].计算机工程,2017,43(1):172-177.
[19]曹玖新,吴江林,石伟,等.新浪微博网信息传播分析与预测[J].计算机学报,2014,37(4):779-790.
[20]WU Huanhuan,CHENG J,HUANG Silu,et al.Path Problems in Temporal Graphs[J].Proceedings of the VLDB Endowment,2013,7(9):721-732.
[21]ZHANG Miao,DAI Chunni,DING C H,et al.Probabilistic Solutions of Influence Propagation on Social Networks[C]//Proceedings of the 22nd ACM International Conference on Information and Knowledge Management.New York,USA:ACM Press,2013:429-438.
[22]VALIANT L G.The Complexity of Enumeration and Reliability Problems[J].SIAM Journal on Computing,1979,8(3):410-421.
编辑金胡考 |