{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T02:48:29Z","timestamp":1781664509191,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2018YFB1800601"],"award-info":[{"award-number":["2018YFB1800601"]}]},{"name":"the National Natural Science Foundation of China","award":["61972219"],"award-info":[{"award-number":["61972219"]}]},{"name":"the RD Program of Shenzhen","award":["JCYJ20190813174403598"],"award-info":[{"award-number":["JCYJ20190813174403598"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,26]]},"DOI":"10.1145\/3459637.3482297","type":"proceedings-article","created":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T15:31:14Z","timestamp":1636990274000},"page":"1243-1252","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":135,"title":["SimpleX"],"prefix":"10.1145","author":[{"given":"Kelong","family":"Mao","sequence":"first","affiliation":[{"name":"Renmin University of China, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinpeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quanyu","family":"Dai","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenhua","family":"Dong","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Xiao","sequence":"additional","affiliation":[{"name":"Tsinghua University, 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"}]}],"member":"320","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Graph Convolutional Matrix Completion. In KDD'18 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 KDD'18 Deep Learning Day. Rianne van den Berg, Thomas N Kipf, and Max Welling. 2018. Graph Convolutional Matrix Completion. In KDD'18 Deep Learning Day."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3373807","article-title":"Efficient Neural Matrix Factorization without Sampling for Recommendation","volume":"38","author":"Chen Chong","year":"2020","unstructured":"Chong Chen , Min Zhang , Yongfeng Zhang , Yiqun Liu , and Shaoping Ma . 2020 . Efficient Neural Matrix Factorization without Sampling for Recommendation . ACM Transactions on Information Systems (TOIS) 38 , 2 (2020), 1 -- 28 . Chong Chen, Min Zhang, Yongfeng Zhang, Yiqun Liu, and Shaoping Ma. 2020. Efficient Neural Matrix Factorization without Sampling for Recommendation. ACM Transactions on Information Systems (TOIS) 38, 2 (2020), 1--28.","journal-title":"ACM Transactions on Information Systems (TOIS)"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080797"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5330"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_2_6_1","volume-title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI). 2230--2236","author":"Ding Jingtao","year":"2019","unstructured":"Jingtao Ding , Yuhan Quan , Xiangnan He , Yong Li , and Depeng Jin . 2019 . Rein-forced Negative Sampling for Recommendation with Exposure Data . In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI). 2230--2236 . Jingtao Ding, Yuhan Quan, Xiangnan He, Yong Li, and Depeng Jin. 2019. Rein-forced Negative Sampling for Recommendation with Exposure Data. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI). 2230--2236."},{"key":"e_1_3_2_2_7_1","volume-title":"Collaborative Memory Network for Recommendation Systems. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR). 515--524","author":"Ebesu Travis","year":"2018","unstructured":"Travis Ebesu , Bin Shen , and Yi Fang . 2018 . Collaborative Memory Network for Recommendation Systems. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR). 515--524 . Travis Ebesu, Bin Shen, and Yi Fang. 2018. Collaborative Memory Network for Recommendation Systems. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR). 515--524."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.100"},{"key":"e_1_3_2_2_9_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Advances in Neural Information Processing Systems (NeurIPS). 1024--1034.  Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Advances in Neural Information Processing Systems (NeurIPS). 1024--1034."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052639"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403253"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186150"},{"key":"e_1_3_2_2_17_1","volume-title":"Disentangled Graph Convolutional Networks. In International Conference on Machine Learning (ICML). 4212--4221","author":"Ma Jianxin","year":"2019","unstructured":"Jianxin Ma , Peng Cui , Kun Kuang , Xin Wang , and Wenwu Zhu . 2019 . Disentangled Graph Convolutional Networks. In International Conference on Machine Learning (ICML). 4212--4221 . Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, and Wenwu Zhu. 2019. Disentangled Graph Convolutional Networks. In International Conference on Machine Learning (ICML). 4212--4221."},{"key":"e_1_3_2_2_18_1","unstructured":"Jianxin Ma Chang Zhou Peng Cui Hongxia Yang and Wenwu Zhu. 2019. Learning Disentangled Representations for Recommendation. In Advances in Neural Information Processing Systems (NeurIPS). 5711--5722.  Jianxin Ma Chang Zhou Peng Cui Hongxia Yang and Wenwu Zhu. 2019. Learning Disentangled Representations for Recommendation. In Advances in Neural Information Processing Systems (NeurIPS). 5711--5722."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3133036"},{"key":"e_1_3_2_2_20_1","unstructured":"Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Advances in Neural Information Processing Systems (NeurIPS). 3111--3119.  Tomas Mikolov Ilya Sutskever Kai Chen Greg S Corrado and Jeff Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Advances in Neural Information Processing Systems (NeurIPS). 3111--3119."},{"key":"e_1_3_2_2_21_1","volume-title":"SLIM: Sparse Linear Methods for Top-N Recommender Systems. In IEEE 11th International Conference on Data Mining (ICDM). 497--506","author":"Ning Xia","year":"2011","unstructured":"Xia Ning and George Karypis . 2011 . SLIM: Sparse Linear Methods for Top-N Recommender Systems. In IEEE 11th International Conference on Data Mining (ICDM). 497--506 . Xia Ning and George Karypis. 2011. SLIM: Sparse Linear Methods for Top-N Recommender Systems. In IEEE 11th International Conference on Data Mining (ICDM). 497--506."},{"key":"e_1_3_2_2_22_1","volume-title":"Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI). 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 (UAI). 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 (UAI). 452--461."},{"key":"e_1_3_2_2_23_1","volume-title":"RecVAE: A New Variational Autoencoder for Top-N Recommen-dations with Implicit Feedback. In The Thirteenth ACM International Conference on Web Search and Data Mining (WSDM). 528--536","author":"Shenbin Ilya","unstructured":"Ilya Shenbin , Anton Alekseev , Elena Tutubalina , Valentin Malykh , and Sergey I. Nikolenko . 2020 . RecVAE: A New Variational Autoencoder for Top-N Recommen-dations with Implicit Feedback. In The Thirteenth ACM International Conference on Web Search and Data Mining (WSDM). 528--536 . Ilya Shenbin, Anton Alekseev, Elena Tutubalina, Valentin Malykh, and Sergey I. Nikolenko. 2020. RecVAE: A New Variational Autoencoder for Top-N Recommen-dations with Implicit Feedback. In The Thirteenth ACM International Conference on Web Search and Data Mining (WSDM). 528--536."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2017.72"},{"key":"e_1_3_2_2_25_1","volume-title":"NGAT4Rec: Neighbor-Aware Graph Attention Network For Recommendation. arXiv preprint arXiv:2010.12256","author":"Song Jinbo","year":"2020","unstructured":"Jinbo Song , Chao Chang , Fei Sun , Xinbo Song , and Peng Jiang . 2020. NGAT4Rec: Neighbor-Aware Graph Attention Network For Recommendation. arXiv preprint arXiv:2010.12256 ( 2020 ). Jinbo Song, Chao Chang, Fei Sun, Xinbo Song, and Peng Jiang. 2020. NGAT4Rec: Neighbor-Aware Graph Attention Network For Recommendation. arXiv preprint arXiv:2010.12256 (2020)."},{"key":"e_1_3_2_2_26_1","volume-title":"Embarrassingly Shallow Autoencoders for Sparse Data. In The World Wide Web Conference (WWW). 3251--3257","author":"Steck Harald","year":"2019","unstructured":"Harald Steck . 2019 . Embarrassingly Shallow Autoencoders for Sparse Data. In The World Wide Web Conference (WWW). 3251--3257 . Harald Steck. 2019. Embarrassingly Shallow Autoencoders for Sparse Data. In The World Wide Web Conference (WWW). 3251--3257."},{"key":"e_1_3_2_2_27_1","volume-title":"Khoshgoftaar","author":"Su Xiaoyuan","year":"2009","unstructured":"Xiaoyuan Su and Taghi M . Khoshgoftaar . 2009 . A Survey of Collaborative Filtering Techniques. Adv. Artif. Intell . 2009 (2009), 421425:1--421425:19. Xiaoyuan Su and Taghi M. Khoshgoftaar. 2009. A Survey of Collaborative Filtering Techniques. Adv. Artif. Intell. 2009 (2009), 421425:1--421425:19."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403254"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401123"},{"key":"e_1_3_2_2_31_1","unstructured":"Petar Veli\u010dkovi\u0107 Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. In International Con-ference on Learning Representations (ICLR).  Petar Veli\u010dkovi\u0107 Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. In International Con-ference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401137"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330665"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_2_36_1","volume-title":"Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. In Companion Proceedings of the Web Conference (WWW). 441--447","author":"Yang Ji","year":"2020","unstructured":"Ji Yang , Xinyang Yi , Derek Zhiyuan Cheng , Lichan Hong , Yang Li , Simon Xiaoming Wang , Taibai Xu , and Ed H Chi . 2020 . Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. In Companion Proceedings of the Web Conference (WWW). 441--447 . Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, and Ed H Chi. 2020. Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. In Companion Proceedings of the Web Conference (WWW). 441--447."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240381"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350995"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_40_1","volume-title":"Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters. In International Conference on Machine Learning (ICML). 10936--10945","author":"Yu Wenhui","year":"2020","unstructured":"Wenhui Yu and Zheng Qin . 2020 . Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters. In International Conference on Machine Learning (ICML). 10936--10945 . Wenhui Yu and Zheng Qin. 2020. Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters. In International Conference on Machine Learning (ICML). 10936--10945."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401155"}],"event":{"name":"CIKM '21: The 30th ACM International Conference on Information and Knowledge Management","location":"Virtual Event Queensland Australia","acronym":"CIKM '21","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482297","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459637.3482297","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:13Z","timestamp":1750191133000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482297"}},"subtitle":["A Simple and Strong Baseline for Collaborative Filtering"],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":41,"alternative-id":["10.1145\/3459637.3482297","10.1145\/3459637"],"URL":"https:\/\/doi.org\/10.1145\/3459637.3482297","relation":{},"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"2021-10-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}