基于神经网络的链路预测算法
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摘要
针对当前基于网络拓扑结构相似性的链路预测算法普遍存在精确度较低且适应性不强的问题,研究发现融合算法能够有效改善这些问题。提出了一种基于神经网络的融合链路预测算法,主要通过神经网络对不同链路预测相似性指标进行融合。该算法使用神经网络对不同相似性指标的数值特征进行学习,同时采用标准粒子群算法对神经网络进行了优化,并通过优化学习后的神经网络模型计算出融合指标。多个真实网络数据集上实验表明,该算法的预测精度明显高于融合之前的各项指标,并且优于现有融合方法的精度。
To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods, a neural network-based link prediction algorithm, which fused similarity indices by neural network was proposed. The algorithm uses neural network to study the numerical characteristics of different similarity indices, and uses particle swarm optimization to optimize the neural network, and calculates the fusion index by the optimized neural network model. The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion, and the accuracy is better than the existing methods.
To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods, a neural network-based link prediction algorithm, which fused similarity indices by neural network was proposed. The algorithm uses neural network to study the numerical characteristics of different similarity indices, and uses particle swarm optimization to optimize the neural network, and calculates the fusion index by the optimized neural network model. The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion, and the accuracy is better than the existing methods.
引文
[1]LüL,ZHOU T.Link prediction in complex networks:a survey[J].Physica a:Statistical Mechanics and its Applications,2011,390(6):1150-1170.
[2]CANNISTRACI C V,ALANISLOBATO G,RAVASI T.From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks[J].Scientific Reports,2015,3(4):1613-1613.
[3]KOSSINETS G.Effects of missing data in social network[J].Social Networks,2006,28(3):247-268.
[4]ESSLIMAMI I,BRUN A,BOYER A.Densifying a behavioral recommender system by social networks link prediction methods[J].Social Network Analysis and Mining,2011,1(3):159-172.
[5]刘树新,季新生,刘彩霞,等.一种信息传播促进网络增长的网络演化模型[J].物理学报,2014,63(15).LIU S X,JI X S,LIU C X,et al.A complex network evolution model for network growth promoted by information transmission[J].Acta Physica Sinica,2014,63(15).
[6]刘树新,季新生,刘彩霞,等.局部拓扑信息耦合促进网络演化[J].电子与信息学报,2016,38(9):2180-2187.LIU S X,JI X S,LIU C X,et al.Information coupling of local topology promoting the network evolution[J].Journal of Electronics&Information Technology,2016,38(9):2180-2187.
[7]ZHOU C,MOTTER A E,KURTHS J.Universality in the synchronization of weighted random networks[J].Physical Review Letters,2006,96(3):034101.
[8]FIRTUNATO S.Community detection in graph[J].Physics Reports,2010,486(3):75-174.
[9]黄立威,李德毅,马于涛,等.一种基于元路径的异质信息网络链路预测模型[J].计算机学报,2014,37(4):848-858.HUANG L W,LI D Y,MA Y T,et al.A meta path-based link prediction model for heterogeneous information networks[J].Chinese Journal of Computers 2014,37(4):848-858.
[10]王守辉,于洪涛,黄瑞阳,等.基于模体演化的时序链路预测方法[J].自动化学报,2016,42(5):735-745.WANG S H,YU H T,HUANG R Y,et al.A temporal link prediction method based on motifevolution[J].Acta Automatica Sinica,2016,42(5):735-745.
[11]MITZENMACHER M.A brief history of generative models for power law and lognormal distributions[J].Internet Mathematics,2004,1(2):226-251.
[12]ADAMIC L A,Adar E.Friends and neighbors on the Web[J].Social Networks,2003,25(3):211-230.
[13]OU Q,JIN Y D,ZHOU T,et al.Power-law strength-degree correlation from resource-allocation dynamics on weighted networks[J].Physical Review E,2007,75(2).
[14]BARABáSI A L,Albert R.Emergence of scaling in random networks[J].Science,1999,286(5439):509-512.
[15]LIU S,JI X,LIU C,et al.Extended resource allocation index for link prediction of complex network[J].Physica a Statistical Mechanics&its Applications,2017,479:174-183.
[16]KATZ L.A new status index derived from sociometric index[J].Psychometrika,1953,18(1):39-43.
[17]LIU S,JI X,LIU C,et al.Similarity indices based on link weight assignment for link prediction of unweighted complex networks[J].International Journal of Modern Physics B,2017,31(2):412-1054.
[18]HE Y,LIU J N K,HU Y,et al.OWA operator based link prediction ensemble for social network[J].Expert Systems with Applications,2015,42(1):21-50.
[19]GAO F,MUSIAL K,COOPER C,et al.Link prediction methods and their accuracy for different social networks and network metrics[J].Scientific Programming,2014,501:172879.
[20]吴祖峰,梁棋,刘峤,等.基于Ada Boost的链路预测优化算法[J].通信学报,2014,35(3):116-123.WU Z F,LIANG Q,LIU Q,et al.Modified link prediction algorithm based on Ada Boost[J].Journal on Communications,2014,35(3):116-123.
[21]YU H T,WANG S H,MA Q Q.Link prediction algorithm based on the Choquet fuzzy integral[J].Journal on Communications,2016,20(4):809-824.
[22]吕琳媛,周涛.链路预测[M].北京:高等教育出版社,2013:46-47.LYU L Y,ZHOU T.Link prediction[M].Beijing:High Education Press,2013.
[23]BRITS R,ENGELBRECHT A P,et al.A niching particle swarm optimizer[C]//The 4th Asia-Pacific conference on simulated evolution and learning,Singapore,2002,692-696.
[24]HECHT-NIELSEN R.Theory of the backpropagation neural network[C]//International Joint Conference on Neural Networks,1989,1(1):593-605.
[2]CANNISTRACI C V,ALANISLOBATO G,RAVASI T.From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks[J].Scientific Reports,2015,3(4):1613-1613.
[3]KOSSINETS G.Effects of missing data in social network[J].Social Networks,2006,28(3):247-268.
[4]ESSLIMAMI I,BRUN A,BOYER A.Densifying a behavioral recommender system by social networks link prediction methods[J].Social Network Analysis and Mining,2011,1(3):159-172.
[5]刘树新,季新生,刘彩霞,等.一种信息传播促进网络增长的网络演化模型[J].物理学报,2014,63(15).LIU S X,JI X S,LIU C X,et al.A complex network evolution model for network growth promoted by information transmission[J].Acta Physica Sinica,2014,63(15).
[6]刘树新,季新生,刘彩霞,等.局部拓扑信息耦合促进网络演化[J].电子与信息学报,2016,38(9):2180-2187.LIU S X,JI X S,LIU C X,et al.Information coupling of local topology promoting the network evolution[J].Journal of Electronics&Information Technology,2016,38(9):2180-2187.
[7]ZHOU C,MOTTER A E,KURTHS J.Universality in the synchronization of weighted random networks[J].Physical Review Letters,2006,96(3):034101.
[8]FIRTUNATO S.Community detection in graph[J].Physics Reports,2010,486(3):75-174.
[9]黄立威,李德毅,马于涛,等.一种基于元路径的异质信息网络链路预测模型[J].计算机学报,2014,37(4):848-858.HUANG L W,LI D Y,MA Y T,et al.A meta path-based link prediction model for heterogeneous information networks[J].Chinese Journal of Computers 2014,37(4):848-858.
[10]王守辉,于洪涛,黄瑞阳,等.基于模体演化的时序链路预测方法[J].自动化学报,2016,42(5):735-745.WANG S H,YU H T,HUANG R Y,et al.A temporal link prediction method based on motifevolution[J].Acta Automatica Sinica,2016,42(5):735-745.
[11]MITZENMACHER M.A brief history of generative models for power law and lognormal distributions[J].Internet Mathematics,2004,1(2):226-251.
[12]ADAMIC L A,Adar E.Friends and neighbors on the Web[J].Social Networks,2003,25(3):211-230.
[13]OU Q,JIN Y D,ZHOU T,et al.Power-law strength-degree correlation from resource-allocation dynamics on weighted networks[J].Physical Review E,2007,75(2).
[14]BARABáSI A L,Albert R.Emergence of scaling in random networks[J].Science,1999,286(5439):509-512.
[15]LIU S,JI X,LIU C,et al.Extended resource allocation index for link prediction of complex network[J].Physica a Statistical Mechanics&its Applications,2017,479:174-183.
[16]KATZ L.A new status index derived from sociometric index[J].Psychometrika,1953,18(1):39-43.
[17]LIU S,JI X,LIU C,et al.Similarity indices based on link weight assignment for link prediction of unweighted complex networks[J].International Journal of Modern Physics B,2017,31(2):412-1054.
[18]HE Y,LIU J N K,HU Y,et al.OWA operator based link prediction ensemble for social network[J].Expert Systems with Applications,2015,42(1):21-50.
[19]GAO F,MUSIAL K,COOPER C,et al.Link prediction methods and their accuracy for different social networks and network metrics[J].Scientific Programming,2014,501:172879.
[20]吴祖峰,梁棋,刘峤,等.基于Ada Boost的链路预测优化算法[J].通信学报,2014,35(3):116-123.WU Z F,LIANG Q,LIU Q,et al.Modified link prediction algorithm based on Ada Boost[J].Journal on Communications,2014,35(3):116-123.
[21]YU H T,WANG S H,MA Q Q.Link prediction algorithm based on the Choquet fuzzy integral[J].Journal on Communications,2016,20(4):809-824.
[22]吕琳媛,周涛.链路预测[M].北京:高等教育出版社,2013:46-47.LYU L Y,ZHOU T.Link prediction[M].Beijing:High Education Press,2013.
[23]BRITS R,ENGELBRECHT A P,et al.A niching particle swarm optimizer[C]//The 4th Asia-Pacific conference on simulated evolution and learning,Singapore,2002,692-696.
[24]HECHT-NIELSEN R.Theory of the backpropagation neural network[C]//International Joint Conference on Neural Networks,1989,1(1):593-605.