[1] WANG S,HU L,WANG Y,et al.Sequential recommender systems:challenges,progress and prospects[J].arXiv:2001.04830,2020.
[2] WANG S J,WANG Y,SHENG Q Z,et al.A survey on session-based recommender systems[J].ACM Computing Surveys,2021,54(7):1-38.
[3] WU Z,PAN S,CHEN F,et al.A comprehensive survey on graph neural networks[J].IEEE Transactions on Neural Networks and Learning Systems,2020,32(1):4-24.
[4] JOAQUIN D,NAOHIR I,TOMOKI U.Content-based collaborative information filtering:actively learning to classify and recommend documents[C]//International Workshop on Cooperative Information Agents.Berlin,Heidelberg:Springer,1998:206-215.
[5] KONSTAN J A,MILLER B N,MALTZ D,et al.GroupLens:applying collaborative filtering to Usenet news[J].Communications of the ACM,1997,40(3):77-87.
[6] LINDEN G,SMITH B,YORK J.Amazon.com recommendations:item-to-item collaborative filtering[J].IEEE Internet Computing,2003,7(1):76-80.
[7] KOREN Y,BELL R,VOLINSKY C.Matrix factorization techniques for recommender systems[J].Computer,2009,42(8):30-37.
[8] KARATZOGLOU A,AMATRIAIN X,BALTRUNAS L,et al.Multiverse recommendation:n-dimensional tensor factorization for context aware collaborative filtering[C]//Proceedings of the Fourth ACM Conference on Recommender Systems,2010:79-86.
[9] RENDLE S.Factorization machines[C]//2010 IEEE International Conference on Data Mining,2010:995-1000.
[10] RENDIE S,FREUDENTHALER C,SCHMIDT-THIEME L.Factorizing personalized Markov chains for next-basket recommendation[C]//Proceedings of the 19th International Conference on World Wide Web,2010:811-820.
[11] ZHAN Z X,ZHONG L L,LIN J,et al.Sequence-aware similarity learning for next-item recommendation[J].The Journal of Supercomputing,2021,77:7509-7534.
[12] XU S Y,GE Y Q,LI Y Q,et al.Causal collaborative filtering[J].arXiv:2102.01868,2021.
[13] HIDASI B,KARATZOGLOU A,BALTRUNAS L,et al.Session-based recommendations with recurrent neural networks[J].arXiv:1511.06939,2015.
[14] LI J,REN P J,CHEN Z M,et al.Neural attentive session-based recommendation[C]//Proceedings of the 2017 ACM on Conference on Information and Knowledge Management,2017:1419-1428.
[15] LIU Q,ZENG Y F,MOKHOSI R,et al.STAMP:short-term attention/memory priority model for session-based recommendation[C]//Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,2018:1831-1839.
[16] WANG M,REN P,MEI L,et al.A collaborative session-based recommendation approach with parallel memory modules[C]//Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval,2019:345-354.
[17] BACH N X,LONG D H,PHUONG T M.Recurrent convolutional networks for session-based recommendations[J].Neurocomputing,2020,411:247-258.
[18] ZHANG J,MA C,MU X,et al.Recurrent convolutional neural network for session-based recommendation[J].Neurocomputing,2021,437:157-167.
[19] GORI M,MONFARDIN G,SCARSELLI F.A new model for learning in graph domains[C]//Proceedings 2005 IEEE International Joint Conference on Neural Networks,2005:729-734.
[20] SCARSELLI F,GORI M,TSOI A C,et al.The graph neural network model[J].IEEE Transactions on Neural Networks,2008,20(1):61-80.
[21] GALLICCHIO C,MICHELIi A.Graph echo state networks[C]//The 2010 International Joint Conference on Neural Networks(IJCNN),2010:1-8.
[22] BRUNA J,ZAREMBA W,SZLAM A,et al.Spectral networks and locally connected networks on graphs[J].arXiv:1312.6203,2013.
[23] 白铂,刘玉婷,马驰骋,等.图神经网络[J].中国科学:数学,2020,50(3):367-384.
BAI B,LIU Y T,MA C C,et al.Graph neural network[J].Science in China:Series A,2020,50(3):367-384.
[24] ZHANG Z,CUI P,ZHU W.Deep learning on graphs:a survey[J].IEEE Transactions on Knowledge and Data Engineering,2020,34(1):249-270.
[25] WU S,TANG Y,ZHU Y,et al.Session-based recommend-ation with graph neural networks[J].arXiv:1811.00855,2018.
[26] XU C,ZHAO P,LIU Y,et al.Graph contextualized self-attention network for session-based recommendation[C]//Proceedings of the Twenty-Eighth International Conference on Artificial Intelligence,2019.
[27] WANG X,WANG R,SHI C,et al.Multi-component graph convolutional collaborative filtering[C]//Proceedings of the AAAI Conference on Artificial Intelligence,2020:6267-6274.
[28] XIAN X,FANG L,SUN S.ReGNN:a repeat aware graph neural network for session-based recommendations[J].IEEE Access,2020,8:98518-98525.
[29] YANG L,LUO L,XIN L,et al.DAGNN:demand-aware graph neural networks for session-based recommendation[J].arXiv:2105.14428,2021.
[30] SARWAR B.Item-based collaborative filtering recommend-ation algorithms[C]//Proceedings of the 10th International Conference on World Wide Web,2001:285-295.
[31] MOLCHANOV P,TYREE S,KARRAS T,et al.Pruning convolutional neural networks for resource efficient inference[J].arXiv:1611.06440,2016.