{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T03:39:51Z","timestamp":1783827591903,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T00:00:00Z","timestamp":1595635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,7,25]]},"DOI":"10.1145\/3397271.3401123","type":"proceedings-article","created":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T07:50:08Z","timestamp":1595663408000},"page":"1289-1298","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":136,"title":["Neighbor Interaction Aware Graph Convolution Networks for Recommendation"],"prefix":"10.1145","author":[{"given":"Jianing","family":"Sun","sequence":"first","affiliation":[{"name":"Huawei Noah's Ark Lab & Montreal Research Center, Montreal, PQ, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingxue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab & Montreal Research Center, Montreal, PQ, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huifeng","family":"Guo","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiming","family":"Tang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuqiang","family":"He","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Ma","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, PQ, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Coates","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, PQ, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"et almbox","author":"Battaglia Peter W","year":"2018","unstructured":"Peter W Battaglia , Jessica B Hamrick , Victor Bapst , Alvaro Sanchez-Gonzalez , Vinicius Zambaldi , Mateusz Malinowski , Andrea Tacchetti , David Raposo , Adam Santoro , Ryan Faulkner , et almbox . 2018 . Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261 (2018). Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, et almbox. 2018. Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261 (2018)."},{"key":"e_1_3_2_1_2_1","volume-title":"Proc. ACM Int. Conf. Web Search and Data Mining.","author":"Beutel Alex","unstructured":"Alex Beutel , Paul Covington , Can Xu , Jia Li , Vince Gatto , and Ed H. Chi . 2018. Latent Cross: Making Use of Context in Recurrent Recommender Systems . In Proc. ACM Int. Conf. Web Search and Data Mining. Alex Beutel, Paul Covington, Can Xu, Jia Li, Vince Gatto, and Ed H. Chi. 2018. Latent Cross: Making Use of Context in Recurrent Recommender Systems. In Proc. ACM Int. Conf. Web Search and Data Mining."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330964"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330673"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347011"},{"key":"e_1_3_2_1_8_1","volume-title":"Proc. Int. Conf. Artificial Intelligence and Statistics.","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio . 2010 . Understanding the difficulty of training deep feedforward neural networks . In Proc. Int. Conf. Artificial Intelligence and Statistics. Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proc. Int. Conf. Artificial Intelligence and Statistics."},{"key":"e_1_3_2_1_9_1","volume-title":"Proc. Int. Joint Conf. Artificial Intelligence.","author":"Gori Marco","year":"2007","unstructured":"Marco Gori and Augusto Pucci . 2007 . ItemRank: A Random-Walk Based Scoring Algorithm for Recommender Engines . In Proc. Int. Joint Conf. Artificial Intelligence. Marco Gori and Augusto Pucci. 2007. ItemRank: A Random-Walk Based Scoring Algorithm for Recommender Engines. In Proc. Int. Joint Conf. Artificial Intelligence."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/239"},{"key":"e_1_3_2_1_11_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems.","author":"Hamilton William","year":"2017","unstructured":"William Hamilton , Rex Ying , and Jure Leskovec . 2017 a. Inductive Representation Learning on Large Graphs . In Proc. Adv. Neural Inf. Proc. Systems. William Hamilton, Rex Ying, and Jure Leskovec. 2017a. Inductive Representation Learning on Large Graphs. In Proc. Adv. Neural Inf. Proc. Systems."},{"key":"e_1_3_2_1_12_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems.","author":"Hamilton William L.","year":"2017","unstructured":"William L. Hamilton , Zhitao Ying , and Jure Leskovec . 2017 b. Inductive Representation Learning on Large Graphs . In Proc. Adv. Neural Inf. Proc. Systems. William L. Hamilton, Zhitao Ying, and Jure Leskovec. 2017b. Inductive Representation Learning on Large Graphs. In Proc. Adv. Neural Inf. Proc. Systems."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883037"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963774"},{"key":"e_1_3_2_1_16_1","volume-title":"Proc. ACM Int. Conf. Information & Knowledge Management.","author":"Huang Po-Sen","unstructured":"Po-Sen Huang , Xiaodong He , Jianfeng Gao , Li Deng , Alex Acero , and Larry P. Heck . 2013. Learning deep structured semantic models for web search using clickthrough data . In Proc. ACM Int. Conf. Information & Knowledge Management. Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry P. Heck. 2013. Learning deep structured semantic models for web search using clickthrough data. In Proc. ACM Int. Conf. Information & Knowledge Management."},{"key":"e_1_3_2_1_17_1","volume-title":"Proc. Int. Conf. Learning Representations.","author":"Thomas","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks . In Proc. Int. Conf. Learning Representations. Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In Proc. Int. Conf. Learning Representations."},{"key":"e_1_3_2_1_18_1","volume-title":"Proc. Int. Conf. Machine Learning (ICML).","author":"Kondor Risi","year":"2018","unstructured":"Risi Kondor and Shubhendu Trivedi . 2018 . On the generalization of equivariance and convolution in neural networks to the action of compact groups . In Proc. Int. Conf. Machine Learning (ICML). Risi Kondor and Shubhendu Trivedi. 2018. On the generalization of equivariance and convolution in neural networks to the action of compact groups. In Proc. Int. Conf. Machine Learning (ICML)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/398"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331283"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_1_24_1","volume-title":"Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining.","author":"Liu Ninghao","year":"2019","unstructured":"Ninghao Liu , Qiaoyu Tan , Yuening Li , Hongxia Yang , Jingren Zhou , and Xia Hu . 2019 b. Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding . In Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining. Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, and Xia Hu. 2019 b. Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding. In Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014424"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5945"},{"key":"e_1_3_2_1_27_1","volume-title":"Proc. Int. Conf. Learning Representations (ICLR).","author":"Maron Haggai","year":"2019","unstructured":"Haggai Maron , Heli Ben-Hamu , Nadav Shamir , and Yaron Lipman . 2019 . Invariant and equivariant graph networks . In Proc. Int. Conf. Learning Representations (ICLR). Haggai Maron, Heli Ben-Hamu, Nadav Shamir, and Yaron Lipman. 2019. Invariant and equivariant graph networks. In Proc. Int. Conf. Learning Representations (ICLR)."},{"key":"e_1_3_2_1_28_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems.","author":"Monti Federico","year":"2017","unstructured":"Federico Monti , Michael Bronstein , and Xavier Bresson . 2017 . Geometric matrix completion with recurrent multi-graph neural networks . In Proc. Adv. Neural Inf. Proc. Systems. Federico Monti, Michael Bronstein, and Xavier Bresson. 2017. Geometric matrix completion with recurrent multi-graph neural networks. In Proc. Adv. Neural Inf. Proc. Systems."},{"key":"e_1_3_2_1_29_1","volume-title":"Factorization Machines. In Proc. IEEE Int. Conf. Data Mining.","author":"Rendle Steffen","year":"2010","unstructured":"Steffen Rendle . 2010 . Factorization Machines. In Proc. IEEE Int. Conf. Data Mining. Steffen Rendle. 2010. Factorization Machines. In Proc. IEEE Int. Conf. Data Mining."},{"key":"e_1_3_2_1_30_1","volume-title":"Proc. Conf. Uncertainty in Artificial Intelligence.","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2009 . BPR: Bayesian Personalized Ranking from Implicit Feedback . In Proc. Conf. Uncertainty in Artificial Intelligence. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In Proc. Conf. Uncertainty in Artificial Intelligence."},{"key":"e_1_3_2_1_31_1","volume-title":"Kantor","author":"Ricci Francesco","year":"2010","unstructured":"Francesco Ricci , Lior Rokach , Bracha Shapira , and Paul B . Kantor . 2010 . Recommender Systems Handbook 1st ed.). Springer-Verlag , Berlin, Heidelberg. Francesco Ricci, Lior Rokach, Bracha Shapira, and Paul B. Kantor. 2010. Recommender Systems Handbook 1st ed.). Springer-Verlag, Berlin, Heidelberg."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290989"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00165"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_35_1","volume-title":"Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (Deep Learning Day).","author":"van den Berg Rianne","year":"2018","unstructured":"Rianne van den Berg , Thomas N Kipf , and Max Welling . 2018 . Graph Convolutional Matrix Completion . In Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (Deep Learning Day). Rianne van den Berg, Thomas N Kipf, and Max Welling. 2018. Graph Convolutional Matrix Completion. In Proc. ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (Deep Learning Day)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186175"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_38_1","volume-title":"Proc. Int. Conf. Learning Representations (ICLR)","volume":"1810","author":"Xu Keyulu","year":"2019","unstructured":"Keyulu Xu , Weihua Hu , Jure Leskovec , and Stefanie Jegelka . 2019 . How Powerful are Graph Neural Networks? . In Proc. Int. Conf. Learning Representations (ICLR) , Vol. abs\/ 1810 .00826. Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2019. How Powerful are Graph Neural Networks?. In Proc. Int. Conf. Learning Representations (ICLR), Vol. abs\/1810.00826."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240381"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015829"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240343"}],"event":{"name":"SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval","location":"Virtual Event China","acronym":"SIGIR '20","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401123","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3397271.3401123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:38Z","timestamp":1750195898000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401123"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,25]]},"references-count":42,"alternative-id":["10.1145\/3397271.3401123","10.1145\/3397271"],"URL":"https:\/\/doi.org\/10.1145\/3397271.3401123","relation":{},"subject":[],"published":{"date-parts":[[2020,7,25]]},"assertion":[{"value":"2020-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}