[1] CUI Peng,WANG Xiao,PEI Jian,et al.A survey on network embedding[J].IEEE Transactions on Knowledge and Data Engineering,2019,31(5):833-852. [2] TU Cunchao,YANG Cheng,LIU Zhiyuan,et al.Overview of network representation learning[J].SCIENTIA SINICA Informationis,2017,47(8):980-996.(in Chinese)涂存超,杨成,刘知远,等.网络表示学习综述[J].中国科学:信息科学,2017,47(8):980-996. [3] CAI H Y,ZHENG V W,CHANG K C C.A comprehensive survey of graph embedding:problems,techniques,and applications[J].IEEE Transactions on Knowledge and Data Engineering,2018,30(9):1616-1637. [4] BHAGAT S,CORMODE G,MUTHUKRISHNAN S.Node classification in social networks[M].Berlin,Germany:Springer,2011. [5] LÜ Linyuan,ZHOU Tao.Link prediction in complex networks:a survey[J].Physica A:Statistical Mechanics and Its Applications,2011,390(6):1150-1170. [6] ROWEIS S T.Nonlinear dimensionality reduction by locally linear embedding[J].Science,2000,290:2323-2326. [7] BELKIN M,NIYOGI P.Laplacian eigenmaps and spectral techniques for embedding and clustering[C]//Proceedings of the 14th International Conference on Neural Information Processing Systems:Natural and Synthetic.New York,USA:ACM Press,2001:585-591. [8] MIKOLOV T,SUTSKEVER I,CHEN K,et al.Distributed representations of words and phrases and their compositionality[EB/OL].[2019-07-11].https://arxiv.org/abs/1310.4546. [9] PEROZZI B,AL-RFOU R,SKIENA S.DeepWalk:online learning of social representations[C]//Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,USA:ACM Press,2014:701-710. [10] TANG Jian,QU Meng,WANG Mingzhe,et al.Line:large-scale information network embedding[C]//Proceedings of the 24th International Conference on World Wide Web.New York,USA:ACM Press,2015:1067-1077. [11] GROVER A,LESKOVEC J.Node2vec:scalable feature learning for networks[C]//Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,USA:ACM Press,2016:855-864. [12] YANG Chen,LIU Ziyuan,ZHAO Deli,et al.Network representation learning with rich text information[C]//Proceedings of the 24th International Joint Conference on Artificial Intelligence.Palo Alto,USA:AAAI Press,2015:2111-2117. [13] HUANG Xiao,LI Jundong,HU Xia.Accelerated attributed network embedding[C]//Proceedings of 2017 SIAM International Conference on Data Mining.Philadelphia,USA:Society for Industrial and Applied Mathematics,2017:633-641. [14] LIU Zhengming,MA Hong,LIU Shuxin,et al.A network representation learning algorithm fusing with textual attribute information of nodes[J].Computer Engineering,2018,44(11):165-171.(in Chinese)刘正铭,马宏,刘树新,等.一种融合节点文本属性信息的网络表示学习算法[J].计算机工程,2018,44(11):165-171. [15] WEN Wen,HUANG Jiaming,CAI Ruichu,et al.Graph embedding by incorporating prior knowledge on vertex information[J].Journal of Software,2018,29(3):786-798.(in Chinese)温雯,黄家明,蔡瑞初,等.一种融合节点先验信息的图表示学习方法[J].软件学报,2018,29(3):786-798. [16] WANG Xiao,CUI Peng,WANG Jing,et al.Community preserving network embedding[C]//Proceedings of the 31st AAAI Conference on Artificial Intelligence.Palo Alto,USA:AAAI Press,2017:203-209. [17] LI Ye,SHA Chaofeng,HUANG Xin,et al.Community detection in attributed graphs:an embedding approach[C]//Proceedings of the 32nd AAAI Conference on Artificial Intelligence.Palo Alto,USA:AAAI Press,2018:338-345. [18] WANG Fei,LI Tao,WANG Xin,et al.Community discovery using nonnegative matrix factorization[J].Data Mining and Knowledge Discovery,2011,22(3):493-521. [19] LESKOVEC J,MCAULEY J J.Learning to discover social circles in ego networks[C]//Proceedings of the 25th International Conference on Neural Information Processing Systems.New York,USA:ACM Press,2012:539-547. [20] ZHANG Lei,QIAN Feng,ZHAO Shu,et al.Network representation learning based on multi-granularity structure[J].CAAI Transactions on Intelligent Systems,2019,14(6):1233-1242.(in Chinese)张蕾,钱峰,赵姝,等.基于多粒度结构的网络表示学习[J].智能系统学报,2019,14(6):1233-1242. |