{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T20:41:11Z","timestamp":1781556071943,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T00:00:00Z","timestamp":1682812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172174,62127808"],"award-info":[{"award-number":["62172174,62127808"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,4,30]]},"DOI":"10.1145\/3543507.3583340","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T23:30:51Z","timestamp":1682551851000},"page":"349-359","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["xGCN: An Extreme Graph Convolutional Network for Large-scale Social Link Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6737-8513","authenticated-orcid":false,"given":"Xiran","family":"Song","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3108-5601","authenticated-orcid":false,"given":"Jianxun","family":"Lian","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5282-551X","authenticated-orcid":false,"given":"Hong","family":"Huang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7142-448X","authenticated-orcid":false,"given":"Zihan","family":"Luo","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5863-962X","authenticated-orcid":false,"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0529-7408","authenticated-orcid":false,"given":"Xue","family":"Lin","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3776-1228","authenticated-orcid":false,"given":"Mingqi","family":"Wu","sequence":"additional","affiliation":[{"name":"Microsoft Gaming, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9867-1712","authenticated-orcid":false,"given":"Chaozhuo","family":"Li","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8608-8482","authenticated-orcid":false,"given":"Xing","family":"Xie","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3934-7605","authenticated-orcid":false,"given":"Hai","family":"Jin","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,4,30]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations. 1\u201312","author":"Alon Uri","year":"2021","unstructured":"Uri Alon and Eran Yahav. 2021. On the Bottleneck of Graph Neural Networks and its Practical Implications. In Proceedings of the 9th International Conference on Learning Representations. 1\u201312."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403296"},{"key":"e_1_3_2_2_3_1","volume-title":"Proceedings of the Annual Conference on Neural Information Processing Systems","author":"Chen Ming","year":"2020","unstructured":"Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, and Ji-Rong Wen. 2020. Scalable Graph Neural Networks via Bidirectional Propagation. In Proceedings of the Annual Conference on Neural Information Processing Systems 2020. 14556\u201314566."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330925"},{"key":"e_1_3_2_2_6_1","volume-title":"Proceedings of the 11th International Conference on Learning Representations. 1\u201312","author":"Fang Yuxin","year":"2023","unstructured":"Yuxin Fang, Li Dong, Hangbo Bao, Xinggang Wang, and Furu Wei. 2023. Corrupted Image Modeling for Self-Supervised Visual Pre-Training. In Proceedings of the 11th International Conference on Learning Representations. 1\u201312."},{"key":"e_1_3_2_2_7_1","volume-title":"Proceedings of Graph Representation Learning and Beyond Workshop at the 37th International Conference on Machine Learning. 1\u20139.","author":"Frasca Fabrizio","year":"2020","unstructured":"Fabrizio Frasca, Emanuele Rossi, Davide Eynard, Ben Chamberlain, Michael Bronstein, and Federico Monti. 2020. SIGN: Scalable Inception Graph Neural Networks. In Proceedings of Graph Representation Learning and Beyond Workshop at the 37th International Conference on Machine Learning. 1\u20139."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_2_10_1","volume-title":"Proceedings of the 31th International Conference on Neural Information Processing Systems. 1024\u20131034","author":"Hamilton L.","year":"2017","unstructured":"William\u00a0L. Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Proceedings of the 31th International Conference on Neural Information Processing Systems. 1024\u20131034."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_13_1","volume-title":"Proceedings of the 5th International Conference on Learning Representations. 1\u201314","author":"N.","unstructured":"Thomas\u00a0N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In Proceedings of the 5th International Conference on Learning Representations. 1\u201314."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_15_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations. 1\u201314","author":"Lepikhin Dmitry","year":"2021","unstructured":"Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen. 2021. GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding. In Proceedings of the 9th International Conference on Learning Representations. 1\u201314."},{"key":"e_1_3_2_2_16_1","first-page":"120","article-title":"PyTorch-BigGraph","volume":"2019","author":"Lerer Adam","year":"2019","unstructured":"Adam Lerer, Ledell Wu, Jiajun Shen, Timoth\u00e9e Lacroix, Luca Wehrstedt, Abhijit Bose, and Alexander Peysakhovich. 2019. PyTorch-BigGraph: A Large-scale Graph Embedding System. In Proceedings of Machine Learning and Systems 2019. 120\u2013131.","journal-title":"A Large-scale Graph Embedding System. In Proceedings of Machine Learning and Systems"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482297"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482291"},{"key":"e_1_3_2_2_19_1","volume-title":"Proceedings of the 1st International Conference on Learning Representations. 1\u201312","author":"Mikolov Tom\u00e1s","year":"2013","unstructured":"Tom\u00e1s Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In Proceedings of the 1st International Conference on Learning Representations. 1\u201312."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/79.543975"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2102141118"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"e_1_3_2_2_24_1","first-page":"2579","article-title":"Visualizing Data Using t-SNE","volume":"9","author":"van\u00a0der Maaten Laurens","year":"2008","unstructured":"Laurens van\u00a0der Maaten and Geoffrey Hinton. 2008. Visualizing Data Using t-SNE. Journal of Machine Learning Research 9, 86 (2008), 2579\u20132605.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_25_1","volume-title":"Proceedings of the 6th International Conference on Learning Representations. 1\u201312","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In Proceedings of the 6th International Conference on Learning Representations. 1\u201312."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611977172.61"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530087"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning. 6861\u20136871","author":"Wu Felix","year":"2019","unstructured":"Felix Wu, Amauri H.\u00a0Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian\u00a0Q. Weinberger. 2019. Simplifying Graph Convolutional Networks. In Proceedings of the 36th International Conference on Machine Learning. 6861\u20136871."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_2_30_1","volume-title":"Proceedings of the 7th International Conference on Learning Representations. 1\u201317","author":"Xu Keyulu","year":"2019","unstructured":"Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2019. How Powerful are Graph Neural Networks?. In Proceedings of the 7th International Conference on Learning Representations. 1\u201317."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00051"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539121"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531982"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00094"},{"key":"e_1_3_2_2_35_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations. 1\u201312","author":"Zhu Hao","year":"2021","unstructured":"Hao Zhu and Piotr Koniusz. 2021. Simple Spectral Graph Convolution. In Proceedings of the 9th International Conference on Learning Representations. 1\u201312."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313508"}],"event":{"name":"WWW '23: The ACM Web Conference 2023","location":"Austin TX USA","acronym":"WWW '23","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2023"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583340","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3543507.3583340","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:23Z","timestamp":1750178243000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3543507.3583340"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,30]]},"references-count":35,"alternative-id":["10.1145\/3543507.3583340","10.1145\/3543507"],"URL":"https:\/\/doi.org\/10.1145\/3543507.3583340","relation":{},"subject":[],"published":{"date-parts":[[2023,4,30]]},"assertion":[{"value":"2023-04-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}