{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T22:42:43Z","timestamp":1778539363375,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T00:00:00Z","timestamp":1741564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3,10]]},"DOI":"10.1145\/3701551.3703522","type":"proceedings-article","created":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T12:30:16Z","timestamp":1740573016000},"page":"419-428","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6010-5436","authenticated-orcid":false,"given":"Chaejeong","family":"Lee","sequence":"first","affiliation":[{"name":"Korea Telecom, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6530-2662","authenticated-orcid":false,"given":"Jeongwhan","family":"Choi","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7954-3128","authenticated-orcid":false,"given":"Hyowon","family":"Wi","sequence":"additional","affiliation":[{"name":"KAIST, Daejeon, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7027-2429","authenticated-orcid":false,"given":"Sung-Bae","family":"Cho","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1268-840X","authenticated-orcid":false,"given":"Noseong","family":"Park","sequence":"additional","affiliation":[{"name":"KAIST, Daejeon, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,3,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Immanuel Bayer Xiangnan He Bhargav Kanagal and Steffen Rendle. 2017. A generic coordinate descent framework for learning from implicit feedback. In TheWebConf (former WWW). 1341--1350.","DOI":"10.1145\/3038912.3052694"},{"key":"e_1_3_2_1_2_1","unstructured":"Xuheng Cai Chao Huang Lianghao Xia and Xubin Ren. 2023. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. In ICLR."},{"key":"e_1_3_2_1_3_1","unstructured":"Jeongwhan Choi Seoyoung Hong Noseong Park and Sung-Bae Cho. 2023a. Blurring-Sharpening Process Models for Collaborative Filtering. In SIGIR."},{"key":"e_1_3_2_1_4_1","unstructured":"Jeongwhan Choi Jinsung Jeon and Noseong Park. 2021. LT-OCF: Learnable-Time ODE-based Collaborative Filtering. In CIKM."},{"key":"e_1_3_2_1_5_1","volume-title":"QoS-Aware Graph Contrastive Learning for Web Service Recommendation. In 2023 30th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 171--180","author":"Choi Jeongwhan","year":"2023","unstructured":"Jeongwhan Choi and Duksan Ryu. 2023. QoS-Aware Graph Contrastive Learning for Web Service Recommendation. In 2023 30th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 171--180."},{"key":"e_1_3_2_1_6_1","volume-title":"RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2312.16563","author":"Choi Jeongwhan","year":"2023","unstructured":"Jeongwhan Choi, Hyowon Wi, Chaejeong Lee, Sung-Bae Cho, Dongha Lee, and Noseong Park. 2023b. RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2312.16563 (2023)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_1_8_1","first-page":"1094","article-title":"Simplify and robustify negative sampling for implicit collaborative filtering","volume":"33","author":"Ding Jingtao","year":"2020","unstructured":"Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, and Depeng Jin. 2020. Simplify and robustify negative sampling for implicit collaborative filtering. Advances in Neural Information Processing Systems, Vol. 33 (2020), 1094--1105.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Wenqi Fan Xiaorui Liu Wei Jin Xiangyu Zhao Jiliang Tang and Qing Li. 2022. Graph Trend Filtering Networks for Recommendation. In SIGIR. 112--121.","DOI":"10.1145\/3477495.3531985"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2827872"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883037"},{"key":"e_1_3_2_1_12_1","unstructured":"Xiangnan He Kuan Deng Xiang Wang Yan Li YongDong Zhang and Meng Wang. 2020. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. In SIGIR."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/227"},{"key":"e_1_3_2_1_14_1","volume-title":"TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering. In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 565--574","author":"Hong Seoyoung","year":"2022","unstructured":"Seoyoung Hong, Minju Jo, Seungji Kook, Jaeeun Jung, Hyowon Wi, Noseong Park, and Sung-Bae Cho. 2022. TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering. In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 565--574."},{"key":"e_1_3_2_1_15_1","volume-title":"MGDCF: Distance learning via markov graph diffusion for neural collaborative filtering","author":"Hu Jun","year":"2024","unstructured":"Jun Hu, Bryan Hooi, Shengsheng Qian, Quan Fang, and Changsheng Xu. 2024. MGDCF: Distance learning via markov graph diffusion for neural collaborative filtering. IEEE Transactions on Knowledge and Data Engineering (2024)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Jui-Ting Huang Ashish Sharma Shuying Sun Li Xia David Zhang Philip Pronin Janani Padmanabhan Giuseppe Ottaviano and Linjun Yang. 2020. Embedding-based retrieval in facebook search. In KDD. 2553--2561.","DOI":"10.1145\/3394486.3403305"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467408"},{"key":"e_1_3_2_1_18_1","volume-title":"Contrastive Self-supervised Learning in Recommender Systems: A Survey. arXiv preprint arXiv: Arxiv-2303.09902","author":"Jing Mengyuan","year":"2023","unstructured":"Mengyuan Jing, Yanmin Zhu, Tianzi Zang, and Ke Wang. 2023. Contrastive Self-supervised Learning in Recommender Systems: A Survey. arXiv preprint arXiv: Arxiv-2303.09902 (2023)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00518"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Taeyong Kong Taeri Kim Jinsung Jeon Jeongwhan Choi Yeon-Chang Lee Noseong Park and Sang-Wook Kim. 2022. Linear or Non-Linear That is the Question!. In WSDM. 517--525.","DOI":"10.1145\/3488560.3498501"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570419"},{"key":"e_1_3_2_1_22_1","volume-title":"SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation. arXiv preprint arXiv:2405.00287","author":"Lee Chaejeong","year":"2024","unstructured":"Chaejeong Lee, Jeongwhan Choi, Hyowon Wi, Sung-Bae Cho, and Noseong Park. 2024a. SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation. arXiv preprint arXiv:2405.00287 (2024)."},{"key":"e_1_3_2_1_23_1","volume-title":"Graph Signal Processing for Cross-Domain Recommendation. arXiv preprint arXiv:2407.12374","author":"Lee Jeongeun","year":"2024","unstructured":"Jeongeun Lee, Seongku Kang, Won-Yong Shin, Jeongwhan Choi, Noseong Park, and Dongha Lee. 2024b. Graph Signal Processing for Cross-Domain Recommendation. arXiv preprint arXiv:2407.12374 (2024)."},{"key":"e_1_3_2_1_24_1","unstructured":"Dongdong Li Zhigang Wang Jian Wang Xinyu Zhang Errui Ding Jingdong Wang and Zhaoxiang Zhang. 2022. Self-Guided Hard Negative Generation for Unsupervised Person Re-Identification. In IJCAI."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Hongjun Lim Yeon-Chang Lee Jin-Seo Lee Sanggyu Han Seunghyeon Kim Yeongjong Jeong Changbong Kim Jaehun Kim Sunghoon Han Solbi Choi et al. 2022. AiRS: a large-scale recommender system at naver news. In ICDE. 3386--3398.","DOI":"10.1109\/ICDE53745.2022.00319"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512104"},{"key":"e_1_3_2_1_27_1","volume-title":"com recommendations: Item-to-item collaborative filtering","author":"Linden Greg","year":"2003","unstructured":"Greg Linden, Brent Smith, and Jeremy York. 2003. Amazon. com recommendations: Item-to-item collaborative filtering. IEEE Internet computing, Vol. 7, 1 (2003), 76--80."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615134"},{"key":"e_1_3_2_1_29_1","unstructured":"Kelong Mao Jieming Zhu Xi Xiao Biao Lu Zhaowei Wang and Xiuqiang He. 2021. UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. In CIKM."},{"key":"e_1_3_2_1_30_1","volume-title":"A Content-Driven Micro-Video Recommendation Dataset at Scale. arXiv preprint arXiv:2309.15379","author":"Ni Yongxin","year":"2023","unstructured":"Yongxin Ni, Yu Cheng, Xiangyan Liu, Junchen Fu, Youhua Li, Xiangnan He, Yongfeng Zhang, and Fajie Yuan. 2023. A Content-Driven Micro-Video Recommendation Dataset at Scale. arXiv preprint arXiv:2309.15379 (2023)."},{"key":"e_1_3_2_1_31_1","volume-title":"Diffusion Recommendation with Implicit Sequence Influence. In Companion Proceedings of the ACM on Web Conference","author":"Niu Yong","year":"2024","unstructured":"Yong Niu, Xing Xing, Zhichun Jia, Ruidi Liu, Mindong Xin, and Jianfu Cui. 2024. Diffusion Recommendation with Implicit Sequence Influence. In Companion Proceedings of the ACM on Web Conference 2024. 1719--1725."},{"key":"e_1_3_2_1_32_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)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle and Christoph Freudenthaler. 2014. Improving pairwise learning for item recommendation from implicit feedback. In WSDM. 273--282.","DOI":"10.1145\/2556195.2556248"},{"key":"e_1_3_2_1_34_1","volume-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI.","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 UAI."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28747"},{"key":"e_1_3_2_1_37_1","unstructured":"Yang Song Jascha Sohl-Dickstein Diederik P Kingma Abhishek Kumar Stefano Ermon and Ben Poole. 2021. Score-Based Generative Modeling through Stochastic Differential Equations. In ICLR."},{"key":"e_1_3_2_1_38_1","unstructured":"Rianne van den Berg Thomas N. Kipf and Max Welling. 2017. Graph Convolutional Matrix Completion. In KDD."},{"key":"e_1_3_2_1_39_1","volume-title":"NeurIPS","volume":"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. NeurIPS, Vol. 30 (2017)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_41_1","unstructured":"Tongzhou Wang and Phillip Isola. 2020. Understanding contrastive representation learning through alignment and uniformity on the hypersphere. In ICML. PMLR 9929--9939."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01376"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019. Neural Graph Collaborative Filtering. In SIGIR.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599370"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"Chuhan Wu Fangzhao Wu Mingxiao An Jianqiang Huang Yongfeng Huang and Xing Xie. 2019. NPA: neural news recommendation with personalized attention. In SIGKDD. 2576--2584.","DOI":"10.1145\/3292500.3330665"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian and Xing Xie. 2021. Self-Supervised Graph Learning for Recommendation. In SIGIR. 726--735.","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_1_47_1","volume-title":"Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering. arXiv preprint arXiv:2306.15905","author":"Wu Xi","year":"2023","unstructured":"Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, and Philip S Yu. 2023c. Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering. arXiv preprint arXiv:2306.15905 (2023)."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612709"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Lianghao Xia Chao Huang Yong Xu Jiashu Zhao Dawei Yin and Jimmy Huang. 2022. Hypergraph contrastive collaborative filtering. In SIGIR. 70--79.","DOI":"10.1145\/3477495.3532058"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Yonghui Yang Zhengwei Wu Le Wu Kun Zhang Richang Hong Zhiqiang Zhang Jun Zhou and Meng Wang. 2023b. Generative-Contrastive Graph Learning for Recommendation. In SIGIR.","DOI":"10.1145\/3539618.3591691"},{"key":"e_1_3_2_1_51_1","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Yang Zhengyi","year":"2023","unstructured":"Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, and Xiangnan He. 2023a. Generate what you prefer: Reshaping sequential recommendation via guided diffusion. Advances in Neural Information Processing Systems, Vol. 36 (2023)."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L. Hamilton and Jure Leskovec. 2018. Graph Convolutional Neural Networks for Web-Scale Recommender Systems. In KDD.","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_53_1","volume-title":"Nguyen Quoc Viet Hung, and H. Yin.","author":"Yu Junliang","year":"2022","unstructured":"Junliang Yu, Xin Xia, Tong Chen, Li zhen Cui, Nguyen Quoc Viet Hung, and H. Yin. 2022a. XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2209.02544 (2022)."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","unstructured":"Junliang Yu Hongzhi Yin Min Gao Xin Xia Xiangliang Zhang and Nguyen Quoc Viet Hung. 2021. Socially-aware self-supervised tri-training for recommendation. In KDD. 2084--2092.","DOI":"10.1145\/3447548.3467340"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"Junliang Yu Hongzhi Yin Xin Xia Tong Chen Lizhen Cui and Quoc Viet Hung Nguyen. 2022b. Are graph augmentations necessary? simple graph contrastive learning for recommendation. In SIGIR. 1294--1303.","DOI":"10.1145\/3477495.3531937"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3282907"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianqi Chen Jun Wang and Yong Yu. 2013. Optimizing top-n collaborative filtering via dynamic negative item sampling. In SIGIR. 785--788.","DOI":"10.1145\/2484028.2484126"}],"event":{"name":"WSDM '25: The Eighteenth ACM International Conference on Web Search and Data Mining","location":"Hannover Germany","acronym":"WSDM '25","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 Eighteenth ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701551.3703522","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3701551.3703522","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:08:48Z","timestamp":1755767328000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701551.3703522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,10]]},"references-count":57,"alternative-id":["10.1145\/3701551.3703522","10.1145\/3701551"],"URL":"https:\/\/doi.org\/10.1145\/3701551.3703522","relation":{},"subject":[],"published":{"date-parts":[[2025,3,10]]},"assertion":[{"value":"2025-03-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}