{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T18:40:06Z","timestamp":1781030406000,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T00:00:00Z","timestamp":1677456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Natural Science Foundation of China (NSFC)","award":["62172106"],"award-info":[{"award-number":["62172106"]}]},{"name":"the National Natural Science Foundation of China (NSFC)","award":["61932007"],"award-info":[{"award-number":["61932007"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,2,27]]},"DOI":"10.1145\/3539597.3570372","type":"proceedings-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T23:27:00Z","timestamp":1677108420000},"page":"805-813","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":57,"title":["CL4CTR: A Contrastive Learning Framework for CTR Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7216-1688","authenticated-orcid":false,"given":"Fangye","family":"Wang","sequence":"first","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1208-9324","authenticated-orcid":false,"given":"Yingxu","family":"Wang","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3103-8442","authenticated-orcid":false,"given":"Dongsheng","family":"Li","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1426-3210","authenticated-orcid":false,"given":"Hansu","family":"Gu","sequence":"additional","affiliation":[{"name":"Independent, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6633-4826","authenticated-orcid":false,"given":"Tun","family":"Lu","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9109-4625","authenticated-orcid":false,"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2915-974X","authenticated-orcid":false,"given":"Ning","family":"Gu","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Bo Chen Yichao Wang Zhirong Liu Ruiming Tang Wei Guo Hongkun Zheng Weiwei Yao Muyu Zhang and Xiuqiang He. 2021a. Enhancing explicit and implicit feature interactions via information sharing for parallel deep CTR models. In CIKM. 3757--3766.","DOI":"10.1145\/3459637.3481915"},{"key":"e_1_3_2_2_2_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 simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482246"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5768"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.552"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/3172077.3172127"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00059"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"e_1_3_2_2_11_1","volume-title":"Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580","author":"Hinton Geoffrey E","year":"2012","unstructured":"Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov. 2012. Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580 (2012)."},{"key":"e_1_3_2_2_12_1","volume-title":"GateNet: Gating-Enhanced Deep Network for Click-Through Rate Prediction. arXiv preprint arXiv:2007.03519","author":"Huang Tongwen","year":"2020","unstructured":"Tongwen Huang, Qingyun She, Zhiqiang Wang, and Junlin Zhang. 2020. GateNet: Gating-Enhanced Deep Network for Click-Through Rate Prediction. arXiv preprint arXiv:2007.03519 (2020)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347043"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959134"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462935"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371785"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313497"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Wantong Lu Yantao Yu Yongzhe Chang Zhen Wang Chenhui Li and Bo Yuan. 2020. A Dual Input-aware Factorization Machine for CTR Prediction. In IJCAI. 3139--3145.","DOI":"10.24963\/ijcai.2020\/434"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401437"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462842"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186040"},{"key":"e_1_3_2_2_23_1","volume-title":"Click-through Rate Prediction with Auto-Quantized Contrastive Learning. arXiv preprint arXiv:2109.13921","author":"Pan Yujie","year":"2021","unstructured":"Yujie Pan, Jiangchao Yao, Bo Han, Kunyang Jia, Ya Zhang, and Hongxia Yang. 2021. Click-through Rate Prediction with Auto-Quantized Contrastive Learning. arXiv preprint arXiv:2109.13921 (2021)."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401440"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3233770"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168771"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242643"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357925"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449930"},{"key":"e_1_3_2_2_30_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_2_31_1","volume-title":"International Conference on Machine Learning. PMLR, 10530--10541","author":"Verma Vikas","year":"2021","unstructured":"Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, and Quoc Le. 2021. Towards domain-agnostic contrastive learning. In International Conference on Machine Learning. PMLR, 10530--10541."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00252"},{"key":"e_1_3_2_2_33_1","volume-title":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Wang Fangye","year":"2022","unstructured":"Fangye Wang, Yingxu Wang, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, and Ning Gu. 2022. Enhancing CTR Prediction with Context-Aware Feature Representation Learning. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_2_35_1","volume-title":"H Chi","author":"Wang Ruoxi","year":"2020","unstructured":"Ruoxi Wang, Rakesh Shivanna, Derek Z Cheng, Sagar Jain, Dong Lin, Lichan Hong, and Ed H Chi. 2020. DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. arXiv preprint arXiv:2008.13535 (2020)."},{"key":"e_1_3_2_2_36_1","volume-title":"International Conference on Machine Learning. PMLR, 9929--9939","author":"Wang Tongzhou","year":"2020","unstructured":"Tongzhou Wang and Phillip Isola. 2020. Understanding contrastive representation learning through alignment and uniformity on the hypersphere. In International Conference on Machine Learning. PMLR, 9929--9939."},{"key":"e_1_3_2_2_37_1","volume-title":"MaskNet: introducing feature-wise multiplication to CTR ranking models by instance-guided mask. arXiv preprint arXiv:2102.07619","author":"Wang Zhiqiang","year":"2021","unstructured":"Zhiqiang Wang, Qingyun She, and Junlin Zhang. 2021. MaskNet: introducing feature-wise multiplication to CTR ranking models by instance-guided mask. arXiv preprint arXiv:2102.07619 (2021)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401304"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"crossref","unstructured":"Jun Xiao Hao Ye Xiangnan He Hanwang Zhang Fei Wu and Tat-Seng Chua. 2017. Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. In IJCAI.","DOI":"10.24963\/ijcai.2017\/435"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"e_1_3_2_2_41_1","volume-title":"Self-Supervised Learning for Recommender Systems: A Survey. arXiv preprint arXiv:2203.15876","author":"Yu Junliang","year":"2022","unstructured":"Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, and Zi Huang. 2022. Self-Supervised Learning for Recommender Systems: A Survey. arXiv preprint arXiv:2203.15876 (2022)."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"crossref","unstructured":"Yantao Yu Zhen Wang and Bo Yuan. 2019. An Input-aware Factorization Machine for Sparse Prediction. In IJCAI. 1466--1472.","DOI":"10.24963\/ijcai.2019\/203"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Jiarui Qin Wei Guo Ruiming Tang and Xiuqiang He. 2021. Deep learning for click-through rate estimation. In IJCAI.","DOI":"10.24963\/ijcai.2021\/636"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412108"},{"key":"e_1_3_2_2_45_1","volume-title":"FINT: Field-Aware Interaction Neural Network for Click-Through Rate Prediction. In ICASSP 2022--2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 3913--3917","author":"Zhao Zhishan","year":"2022","unstructured":"Zhishan Zhao, Sen Yang, Guohui Liu, Dawei Feng, and Kele Xu. 2022. FINT: Field-Aware Interaction Neural Network for Click-Through Rate Prediction. In ICASSP 2022--2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 3913--3917."},{"key":"e_1_3_2_2_46_1","volume-title":"SelfCF: A Simple Framework for Self-supervised Collaborative Filtering. arXiv preprint arXiv:2107.03019","author":"Zhou Xin","year":"2021","unstructured":"Xin Zhou, Aixin Sun, Yong Liu, Jie Zhang, and Chunyan Miao. 2021. SelfCF: A Simple Framework for Self-supervised Collaborative Filtering. arXiv preprint arXiv:2107.03019 (2021). io"}],"event":{"name":"WSDM '23: The Sixteenth ACM International Conference on Web Search and Data Mining","location":"Singapore Singapore","acronym":"WSDM '23","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539597.3570372","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3539597.3570372","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:29Z","timestamp":1750182689000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539597.3570372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,27]]},"references-count":46,"alternative-id":["10.1145\/3539597.3570372","10.1145\/3539597"],"URL":"https:\/\/doi.org\/10.1145\/3539597.3570372","relation":{},"subject":[],"published":{"date-parts":[[2023,2,27]]},"assertion":[{"value":"2023-02-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}