{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:40:17Z","timestamp":1769560817216,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["No.202208330093"],"award-info":[{"award-number":["No.202208330093"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The NEC C&C Foundation","award":["24-004"],"award-info":[{"award-number":["24-004"]}]},{"DOI":"10.13039\/501100006374","name":"JKA Foundation","doi-asserted-by":"publisher","award":["2023M-401"],"award-info":[{"award-number":["2023M-401"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,10]]},"DOI":"10.1145\/3626772.3657799","type":"proceedings-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T12:40:05Z","timestamp":1720701605000},"page":"405-415","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["CaDRec: Contextualized and Debiased Recommender Model"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4491-8369","authenticated-orcid":false,"given":"Xinfeng","family":"Wang","sequence":"first","affiliation":[{"name":"University of Yamanashi, Kofu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7858-6206","authenticated-orcid":false,"given":"Fumiyo","family":"Fukumoto","sequence":"additional","affiliation":[{"name":"University of Yamanashi, Kofu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9575-3678","authenticated-orcid":false,"given":"Jin","family":"Cui","sequence":"additional","affiliation":[{"name":"University of Yamanashi, Kofu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5466-7351","authenticated-orcid":false,"given":"Yoshimi","family":"Suzuki","sequence":"additional","affiliation":[{"name":"University of Yamanashi, Kofu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4997-3850","authenticated-orcid":false,"given":"Jiyi","family":"Li","sequence":"additional","affiliation":[{"name":"University of Yamanashi, Kofu, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8919-1613","authenticated-orcid":false,"given":"Dongjin","family":"Yu","sequence":"additional","affiliation":[{"name":"Hangzhou Dianzi University, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. In The Eleventh International Conference on Learning Representations.","author":"Cai Xuheng","year":"2023","unstructured":"Xuheng Cai, Chao Huang, Lianghao Xia, and Xubin Ren. 2023. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531967"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3473321"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116234"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531952"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539240"},{"key":"e_1_3_2_1_7_1","volume-title":"Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572","author":"Goodfellow Ian J","year":"2014","unstructured":"Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 (2014)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441738"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511969"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21324"},{"key":"e_1_3_2_1_12_1","first-page":"2268","article-title":"Not too little, not too much: a theoretical analysis of graph (over) smoothing","volume":"35","author":"Keriven Nicolas","year":"2022","unstructured":"Nicolas Keriven. 2022. Not too little, not too much: a theoretical analysis of graph (over) smoothing. Advances in Neural Information Processing Systems 35 (2022), 2268--2281.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_13_1","volume-title":"Be causal: De-biasing social network confounding in recommendation. ACM Transactions on Knowledge Discovery from Data 17, 1","author":"Li Qian","year":"2023","unstructured":"Qian Li, Xiangmeng Wang, Zhichao Wang, and Guandong Xu. 2023. Be causal: De-biasing social network confounding in recommendation. ACM Transactions on Knowledge Discovery from Data 17, 1 (2023), 1--23."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462966"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512104"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474263"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3568030"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449986"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271733"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532014"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498433"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM54844.2022.00054"},{"key":"e_1_3_2_1_23_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv:1205.2618","author":"Rendle Steffen","year":"2012","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2012. BPR: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv:1205.2618 (2012)."},{"key":"e_1_3_2_1_24_1","volume-title":"International Conference on Machine Learning. PMLR, 32273--32287","author":"Song Zifan","year":"2023","unstructured":"Zifan Song, Xiao Gong, Guosheng Hu, and Cairong Zhao. 2023. Deep perturbation learning: enhancing the network performance via image perturbations. In International Conference on Machine Learning. PMLR, 32273--32287."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20824"},{"key":"e_1_3_2_1_26_1","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of machine learning research 9, 11 (2008).","journal-title":"Journal of machine learning research"},{"key":"e_1_3_2_1_27_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","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. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539253"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591663"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591678"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03858-w"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3594633"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_1_34_1","first-page":"3870","article-title":"PD-GAN: Adversarial learning for personalized diversity-promoting recommendation","volume":"19","author":"Wu Qiong","year":"2019","unstructured":"Qiong Wu, Yong Liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, and Lu Guan. 2019. PD-GAN: Adversarial learning for personalized diversity-promoting recommendation.. In IJCAI, Vol. 19. 3870--3876.","journal-title":"IJCAI"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583336"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532058"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539473"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557431"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591770"},{"key":"e_1_3_2_1_40_1","volume-title":"Nguyen Quoc Viet Hung, and Hongzhi Yin","author":"Yu Junliang","year":"2023","unstructured":"Junliang Yu, Xin Xia, Tong Chen, Lizhen Cui, Nguyen Quoc Viet Hung, and Hongzhi Yin. 2023. XSimGCL: Towards extremely simple graph contrastive learning for recommendation. IEEE Transactions on Knowledge and Data Engineering (2023)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467340"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449844"},{"key":"e_1_3_2_1_43_1","volume-title":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1294--1303","author":"Yu Junliang","year":"2022","unstructured":"Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, and Quoc Viet Hung Nguyen. 2022. Are graph augmentations necessary? simple graph contrastive learning for recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1294--1303."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20878"},{"key":"e_1_3_2_1_45_1","first-page":"7866","article-title":"Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering","volume":"35","author":"Zhang An","year":"2022","unstructured":"An Zhang, Wenchang Ma, Xiang Wang, and Tat-Seng Chua. 2022. Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering. In Advances in Neural Information Processing Systems, Vol. 35. 7866--7878.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583461"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583260"},{"key":"e_1_3_2_1_48_1","unstructured":"Yifei Zhang Hao Zhu Zixing Song Piotr Koniusz Irwin King et al. 2024. Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_1_49_1","first-page":"1","article-title":"Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation","volume":"01","author":"Zhao Zihao","year":"2022","unstructured":"Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, and Wei Wu. 2022. Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation. IEEE Transactions on Knowledge & Data Engineering 01 (2022), 1--13.","journal-title":"IEEE Transactions on Knowledge & Data Engineering"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449788"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591635"}],"event":{"name":"SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Washington DC USA","acronym":"SIGIR 2024","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657799","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3626772.3657799","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:43:17Z","timestamp":1755841397000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":51,"alternative-id":["10.1145\/3626772.3657799","10.1145\/3626772"],"URL":"https:\/\/doi.org\/10.1145\/3626772.3657799","relation":{},"subject":[],"published":{"date-parts":[[2024,7,10]]},"assertion":[{"value":"2024-07-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}