{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T14:57:29Z","timestamp":1775228249709,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Australian Research Council","award":["IC200100022"],"award-info":[{"award-number":["IC200100022"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP190101985"],"award-info":[{"award-number":["DP190101985"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,14]]},"DOI":"10.1145\/3447548.3467340","type":"proceedings-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T06:12:05Z","timestamp":1628748725000},"page":"2084-2092","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":198,"title":["Socially-Aware Self-Supervised Tri-Training for Recommendation"],"prefix":"10.1145","author":[{"given":"Junliang","family":"Yu","sequence":"first","affiliation":[{"name":"The University of Queesland, Brisbane, QLD, Australia"}]},{"given":"Hongzhi","family":"Yin","sequence":"additional","affiliation":[{"name":"The University of Queensland, Brisbane, QLD, Australia"}]},{"given":"Min","family":"Gao","sequence":"additional","affiliation":[{"name":"Chongqing University, Chongqing, China"}]},{"given":"Xin","family":"Xia","sequence":"additional","affiliation":[{"name":"The University of Queensland, Brisbane, QLD, Australia"}]},{"given":"Xiangliang","family":"Zhang","sequence":"additional","affiliation":[{"name":"King Abdullah University of Science and Technology, Thuwal, Saudi Arabia"}]},{"given":"Nguyen Quoc","family":"Viet Hung","sequence":"additional","affiliation":[{"name":"Griffith University, Gold Coast, Australia"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Philip Bachman R Devon Hjelm and William Buchwalter. 2019. Learning representations by maximizing mutual information across views. In Advances in Neural Information Processing Systems. 15535--15545.  Philip Bachman R Devon Hjelm and William Buchwalter. 2019. Learning representations by maximizing mutual information across views. In Advances in Neural Information Processing Systems. 15535--15545."},{"key":"e_1_3_2_2_2_1","volume-title":"Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263","author":"van den Berg Rianne","year":"2017","unstructured":"Rianne van den Berg , Thomas N Kipf , and Max Welling . 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263 ( 2017 ). Rianne van den Berg, Thomas N Kipf, and Max Welling. 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263 (2017)."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279962"},{"key":"e_1_3_2_2_4_1","volume-title":"2020 b. Social boosted recommendation with folded bipartite network embedding","author":"Chen Hongxu","year":"2020","unstructured":"Hongxu Chen , Hongzhi Yin , Tong Chen , Weiqing Wang , Xue Li , and Xia Hu . 2020 b. Social boosted recommendation with folded bipartite network embedding . IEEE Transactions on Knowledge and Data Engineering ( 2020 ). Hongxu Chen, Hongzhi Yin, Tong Chen, Weiqing Wang, Xue Li, and Xia Hu. 2020 b. Social boosted recommendation with folded bipartite network embedding. IEEE Transactions on Knowledge and Data Engineering (2020)."},{"key":"e_1_3_2_2_5_1","volume-title":"International conference on machine learning. PMLR, 1597--1607","author":"Chen Ting","year":"2020","unstructured":"Ting Chen , Simon Kornblith , Mohammad Norouzi , and Geoffrey Hinton . 2020 a. A simple framework for contrastive learning of visual representations . In International conference on machine learning. PMLR, 1597--1607 . Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 a. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607."},{"key":"e_1_3_2_2_6_1","volume-title":"An introduction to the bootstrap","author":"Efron Bradley","unstructured":"Bradley Efron and Robert J Tibshirani . 1994. An introduction to the bootstrap . CRC press . Bradley Efron and Robert J Tibshirani. 1994. An introduction to the bootstrap. CRC press."},{"key":"e_1_3_2_2_7_1","volume-title":"Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton , Rex Ying , and Jure Leskovec . 2017. Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216 ( 2017 ). William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216 (2017)."},{"key":"e_1_3_2_2_8_1","volume-title":"Self-supervised co-training for video representation learning. arXiv preprint arXiv:2010.09709","author":"Han Tengda","year":"2020","unstructured":"Tengda Han , Weidi Xie , and Andrew Zisserman . 2020. Self-supervised co-training for video representation learning. arXiv preprint arXiv:2010.09709 ( 2020 ). Tengda Han, Weidi Xie, and Andrew Zisserman. 2020. Self-supervised co-training for video representation learning. arXiv preprint arXiv:2010.09709 (2020)."},{"key":"e_1_3_2_2_9_1","volume-title":"Contrastive Multi-View Representation Learning on Graphs. arXiv preprint arXiv:2006.05582","author":"Hassani Kaveh","year":"2020","unstructured":"Kaveh Hassani and Amir Hosein Khasahmadi . 2020. Contrastive Multi-View Representation Learning on Graphs. arXiv preprint arXiv:2006.05582 ( 2020 ). Kaveh Hassani and Amir Hosein Khasahmadi. 2020. Contrastive Multi-View Representation Learning on Graphs. arXiv preprint arXiv:2006.05582 (2020)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_12_1","volume-title":"Learning deep representations by mutual information estimation and maximization. arXiv preprint arXiv:1808.06670","author":"Hjelm R Devon","year":"2018","unstructured":"R Devon Hjelm , Alex Fedorov , Samuel Lavoie-Marchildon , Karan Grewal , Phil Bachman , Adam Trischler , and Yoshua Bengio . 2018. Learning deep representations by mutual information estimation and maximization. arXiv preprint arXiv:1808.06670 ( 2018 ). R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio. 2018. Learning deep representations by mutual information estimation and maximization. arXiv preprint arXiv:1808.06670 (2018)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2576940"},{"key":"e_1_3_2_2_14_1","volume-title":"Self-supervised learning on graphs: Deep insights and new direction. arXiv preprint arXiv:2006.10141","author":"Jin Wei","year":"2020","unstructured":"Wei Jin , Tyler Derr , Haochen Liu , Yiqi Wang , Suhang Wang , Zitao Liu , and Jiliang Tang . 2020. Self-supervised learning on graphs: Deep insights and new direction. arXiv preprint arXiv:2006.10141 ( 2020 ). Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, and Jiliang Tang. 2020. Self-supervised learning on graphs: Deep insights and new direction. arXiv preprint arXiv:2006.10141 (2020)."},{"key":"e_1_3_2_2_15_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling . 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 ( 2016 ). Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_2_16_1","volume-title":"Albert: A lite bert for self-supervised learning of language representations. arXiv preprint arXiv:1909.11942","author":"Lan Zhenzhong","year":"2019","unstructured":"Zhenzhong Lan , Mingda Chen , Sebastian Goodman , Kevin Gimpel , Piyush Sharma , and Radu Soricut . 2019 . Albert: A lite bert for self-supervised learning of language representations. arXiv preprint arXiv:1909.11942 (2019). Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019. Albert: A lite bert for self-supervised learning of language representations. arXiv preprint arXiv:1909.11942 (2019)."},{"key":"e_1_3_2_2_17_1","volume-title":"Self-supervised learning: Generative or contrastive. arXiv preprint arXiv:2006.08218","author":"Liu Xiao","year":"2020","unstructured":"Xiao Liu , Fanjin Zhang , Zhenyu Hou , Zhaoyu Wang , Li Mian , Jing Zhang , and Jie Tang . 2020. Self-supervised learning: Generative or contrastive. arXiv preprint arXiv:2006.08218 , Vol. 1 , 2 ( 2020 ). Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, and Jie Tang. 2020. Self-supervised learning: Generative or contrastive. arXiv preprint arXiv:2006.08218, Vol. 1, 2 (2020)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1935826.1935877"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403091"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.soc.27.1.415"},{"key":"e_1_3_2_2_21_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord , Yazhe Li , and Oriol Vinyals . 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 ( 2018 ). Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380112"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403168"},{"key":"e_1_3_2_2_24_1","volume-title":"Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence. AUAI Press, 452--461","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 Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence. AUAI Press, 452--461 . Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence. AUAI Press, 452--461."},{"key":"e_1_3_2_2_25_1","volume-title":"GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation. arXiv preprint arXiv:2006.03736","author":"Sankar Aravind","year":"2020","unstructured":"Aravind Sankar , Yanhong Wu , Yuhang Wu , Wei Zhang , Hao Yang , and Hari Sundaram . 2020. GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation. arXiv preprint arXiv:2006.03736 ( 2020 ). Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei Zhang, Hao Yang, and Hari Sundaram. 2020. GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation. arXiv preprint arXiv:2006.03736 (2020)."},{"key":"e_1_3_2_2_26_1","volume-title":"Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels. arXiv preprint arXiv:1902.11038","author":"Sun Ke","year":"2019","unstructured":"Ke Sun , Zhouchen Lin , and Zhanxing Zhu . 2019. Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels. arXiv preprint arXiv:1902.11038 ( 2019 ). Ke Sun, Zhouchen Lin, and Zhanxing Zhu. 2019. Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels. arXiv preprint arXiv:1902.11038 (2019)."},{"key":"e_1_3_2_2_27_1","unstructured":"Petar Velickovic William Fedus William L Hamilton Pietro Li\u00f2 Yoshua Bengio and R Devon Hjelm. 2019. Deep Graph Infomax.. In ICLR (Poster).  Petar Velickovic William Fedus William L Hamilton Pietro Li\u00f2 Yoshua Bengio and R Devon Hjelm. 2019. Deep Graph Infomax.. In ICLR (Poster)."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_29_1","volume-title":"2020 c. Self-supervised Graph Learning for Recommendation. arXiv preprint arXiv:2010.10783","author":"Wu Jiancan","year":"2020","unstructured":"Jiancan Wu , Xiang Wang , Fuli Feng , Xiangnan He , Liang Chen , Jianxun Lian , and Xing Xie . 2020 c. Self-supervised Graph Learning for Recommendation. arXiv preprint arXiv:2010.10783 ( 2020 ). Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, and Xing Xie. 2020 c. Self-supervised Graph Learning for Recommendation. arXiv preprint arXiv:2010.10783 (2020)."},{"key":"e_1_3_2_2_30_1","volume-title":"2020 a. DiffNet: A Neural Influence and Interest Diffusion Network for Social Recommendation. arXiv preprint arXiv:2002.00844","author":"Wu Le","year":"2020","unstructured":"Le Wu , Junwei Li , Peijie Sun , Yong Ge , and Meng Wang . 2020 a. DiffNet: A Neural Influence and Interest Diffusion Network for Social Recommendation. arXiv preprint arXiv:2002.00844 ( 2020 ). Le Wu, Junwei Li, Peijie Sun, Yong Ge, and Meng Wang. 2020 a. DiffNet: A Neural Influence and Interest Diffusion Network for Social Recommendation. arXiv preprint arXiv:2002.00844 (2020)."},{"key":"e_1_3_2_2_31_1","volume-title":"2019 a. A Neural Influence Diffusion Model for Social Recommendation. CoRR","author":"Wu Le","year":"2019","unstructured":"Le Wu , Peijie Sun , Yanjie Fu , Richang Hong , Xiting Wang , and Meng Wang . 2019 a. A Neural Influence Diffusion Model for Social Recommendation. CoRR , Vol. abs\/ 1904 .10322 ( 2019 ). Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, and Meng Wang. 2019 a. A Neural Influence Diffusion Model for Social Recommendation. CoRR, Vol. abs\/1904.10322 (2019)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"e_1_3_2_2_33_1","volume-title":"2020 d. Graph Neural Networks in Recommender Systems: A Survey. arXiv preprint arXiv:2011.02260","author":"Wu Shiwen","year":"2020","unstructured":"Shiwen Wu , Wentao Zhang , Fei Sun , and Bin Cui . 2020 d. Graph Neural Networks in Recommender Systems: A Survey. arXiv preprint arXiv:2011.02260 ( 2020 ). Shiwen Wu, Wentao Zhang, Fei Sun, and Bin Cui. 2020 d. Graph Neural Networks in Recommender Systems: A Survey. arXiv preprint arXiv:2011.02260 (2020)."},{"key":"e_1_3_2_2_34_1","volume-title":"2020 b. A comprehensive survey on graph neural networks","author":"Wu Zonghan","year":"2020","unstructured":"Zonghan Wu , Shirui Pan , Fengwen Chen , Guodong Long , Chengqi Zhang , and S Yu Philip . 2020 b. A comprehensive survey on graph neural networks . IEEE Transactions on Neural Networks and Learning Systems ( 2020 ). Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip. 2020 b. A comprehensive survey on graph neural networks. IEEE Transactions on Neural Networks and Learning Systems (2020)."},{"key":"e_1_3_2_2_35_1","volume-title":"Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. arXiv preprint arXiv:2012.06852","author":"Xia Xin","year":"2020","unstructured":"Xin Xia , Hongzhi Yin , Junliang Yu , Qinyong Wang , Lizhen Cui , and Xiangliang Zhang . 2020. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. arXiv preprint arXiv:2012.06852 ( 2020 ). Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. 2020. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. arXiv preprint arXiv:2012.06852 (2020)."},{"key":"e_1_3_2_2_36_1","volume-title":"Self-Supervised Reinforcement Learning for Recommender Systems. arXiv preprint arXiv:2006.05779","author":"Xin Xin","year":"2020","unstructured":"Xin Xin , Alexandros Karatzoglou , Ioannis Arapakis , and Joemon M Jose . 2020. Self-Supervised Reinforcement Learning for Recommender Systems. arXiv preprint arXiv:2006.05779 ( 2020 ). Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, and Joemon M Jose. 2020. Self-Supervised Reinforcement Learning for Recommender Systems. arXiv preprint arXiv:2006.05779 (2020)."},{"key":"e_1_3_2_2_37_1","volume-title":"Felix Yu, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Evan Ettinger, et almbox.","author":"Yao Tiansheng","year":"2020","unstructured":"Tiansheng Yao , Xinyang Yi , Derek Zhiyuan Cheng , Felix Yu, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Evan Ettinger, et almbox. 2020 . Self-supervised Learning for Deep Models in Recommendations . arXiv preprint arXiv:2007.12865 (2020). Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Evan Ettinger, et almbox. 2020. Self-supervised Learning for Deep Models in Recommendations. arXiv preprint arXiv:2007.12865 (2020)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2699670"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2580511"},{"key":"e_1_3_2_2_40_1","volume-title":"Advances in Neural Information Processing Systems","volume":"33","author":"You Yuning","year":"2020","unstructured":"Yuning You , Tianlong Chen , Yongduo Sui , Ting Chen , Zhangyang Wang , and Yang Shen . 2020 . Graph Contrastive Learning with Augmentations . Advances in Neural Information Processing Systems , Vol. 33 (2020). Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, and Yang Shen. 2020. Graph Contrastive Learning with Augmentations. Advances in Neural Information Processing Systems, Vol. 33 (2020)."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271725"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00087"},{"key":"e_1_3_2_2_43_1","volume-title":"Enhance Social Recommendation with Adversarial Graph Convolutional Networks. arXiv preprint arXiv:2004.02340","author":"Yu Junliang","year":"2020","unstructured":"Junliang Yu , Hongzhi Yin , Jundong Li , Min Gao , Zi Huang , and Lizhen Cui . 2020. Enhance Social Recommendation with Adversarial Graph Convolutional Networks. arXiv preprint arXiv:2004.02340 ( 2020 ). Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, and Lizhen Cui. 2020. Enhance Social Recommendation with Adversarial Graph Convolutional Networks. arXiv preprint arXiv:2004.02340 (2020)."},{"key":"e_1_3_2_2_44_1","volume-title":"Nguyen Quoc Viet Hung, and Xiangliang Zhang","author":"Yu Junliang","year":"2021","unstructured":"Junliang Yu , Hongzhi Yin , Jundong Li , Qinyong Wang , Nguyen Quoc Viet Hung, and Xiangliang Zhang . 2021 . Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation . arXiv preprint arXiv:2101.06448 (2021). Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang. 2021. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. arXiv preprint arXiv:2101.06448 (2021)."},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00156"},{"key":"e_1_3_2_2_46_1","volume-title":"Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen.","author":"Zhou Kun","year":"2020","unstructured":"Kun Zhou , Hui Wang , Wayne Xin Zhao , Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen. 2020 . S 3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization . arXiv preprint arXiv:2008.07873 (2020). Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen. 2020. S 3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. arXiv preprint arXiv:2008.07873 (2020)."},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.186"}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event Singapore","acronym":"KDD '21","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467340","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3467340","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:23Z","timestamp":1750191503000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467340"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":47,"alternative-id":["10.1145\/3447548.3467340","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3467340","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}