{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T19:36:19Z","timestamp":1780774579223,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"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":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539229","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:41Z","timestamp":1660331201000},"page":"1233-1241","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":102,"title":["CrossCBR"],"prefix":"10.1145","author":[{"given":"Yunshan","family":"Ma","sequence":"first","affiliation":[{"name":"Sea-NExT Joint Lab &amp; National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingzhi","family":"He","sequence":"additional","affiliation":[{"name":"Sea-NExT Joint Lab &amp; National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"An","family":"Zhang","sequence":"additional","affiliation":[{"name":"Sea-NExT Joint Lab &amp; National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tat-Seng","family":"Chua","sequence":"additional","affiliation":[{"name":"Sea-NExT Joint Lab &amp; National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Jinze Bai Chang Zhou Junshuai Song Xiaoru Qu Weiting An Zhao Li and Jun Gao. 2019. Personalized Bundle List Recommendation. In WWW. ACM 60--71.","DOI":"10.1145\/3308558.3313568"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Da Cao Liqiang Nie Xiangnan He Xiaochi Wei Shunzhi Zhu and Tat-Seng Chua. 2017. Embedding Factorization Models for Jointly Recommending Items and User Generated Lists. In SIGIR. ACM 585--594.","DOI":"10.1145\/3077136.3080779"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Jianxin Chang Chen Gao Xiangnan He Depeng Jin and Yong Li. 2020. Bundle Recommendation with Graph Convolutional Networks. In SIGIR. ACM 1673--1676.","DOI":"10.1145\/3397271.3401198"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3114586"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Liang Chen Yang Liu Xiangnan He Lianli Gao and Zibin Zheng. 2019 c. Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network.. In IJCAI. 2095--2101.","DOI":"10.24963\/ijcai.2019\/290"},{"key":"e_1_3_2_1_6_1","volume-title":"Hinton","author":"Chen Ting","year":"2020","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In ICML (Proceedings of Machine Learning Research, Vol. 119). PMLR , 1597--1607."},{"key":"e_1_3_2_1_7_1","first-page":"2116","article-title":"a. Semi-supervised User Profiling with Heterogeneous Graph Attention Networks","volume":"19","author":"Chen Weijian","year":"2019","unstructured":"Weijian Chen, Yulong Gu, Zhaochun Ren, Xiangnan He, Hongtao Xie, Tong Guo, Dawei Yin, and Yongdong Zhang. 2019 a. Semi-supervised User Profiling with Heterogeneous Graph Attention Networks.. In IJCAI , Vol. 19. 2116--2122.","journal-title":"IJCAI"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Wen Chen Pipei Huang Jiaming Xu Xin Guo Cheng Guo Fei Sun Chao Li Andreas Pfadler Huan Zhao and Binqiang Zhao. 2019 b. POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. In KDD. ACM 2662--2670.","DOI":"10.1145\/3292500.3330652"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Qilin Deng Kai Wang Minghao Zhao Zhene Zou Runze Wu Jianrong Tao Changjie Fan and Liang Chen. 2020. Personalized Bundle Recommendation in Online Games. In CIKM. ACM 2381--2388.","DOI":"10.1145\/3340531.3412734"},{"key":"e_1_3_2_1_10_1","volume-title":"Wai Keung Wong, and Tat-Seng Chua","author":"Ding Yujuan","year":"2021","unstructured":"Yujuan Ding, Yunshan Ma, Wai Keung Wong, and Tat-Seng Chua. 2021. Leveraging Two Types of Global Graph for Sequential Fashion Recommendation. In ICMR. ACM, 73--81."},{"key":"e_1_3_2_1_11_1","volume-title":"EMNLP (1)","author":"Gao Tianyu","unstructured":"Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021. SimCSE: Simple Contrastive Learning of Sentence Embeddings. In EMNLP (1). Association for Computational Linguistics, 6894--6910."},{"key":"e_1_3_2_1_12_1","volume-title":"AISTATS (JMLR Proceedings","volume":"256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In AISTATS (JMLR Proceedings, Vol. 9). JMLR.org, 249--256."},{"key":"e_1_3_2_1_13_1","volume-title":"AISTATS (JMLR Proceedings","volume":"304","author":"Gutmann Michael","year":"2010","unstructured":"Michael Gutmann and Aapo Hyv\"a rinen. 2010. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. In AISTATS (JMLR Proceedings, Vol. 9). JMLR.org, 297--304."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Xiangnan He Kuan Deng Xiang Wang Yan Li Yong-Dong Zhang and Meng Wang. 2020. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. In SIGIR. ACM 639--648.","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_15_1","unstructured":"R. Devon Hjelm Alex Fedorov Samuel Lavoie-Marchildon Karan Grewal Philip Bachman Adam Trischler and Yoshua Bengio. 2019. Learning deep representations by mutual information estimation and maximization. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_16_1","unstructured":"Haoji Hu Xiangnan He Jinyang Gao and Zhi-Li Zhang. 2020. Modeling Personalized Item Frequency Information for Next-basket Recommendation. In SIGIR. ACM 1071--1080."},{"key":"e_1_3_2_1_17_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Chen Li Yuanfu Lu Wei Wang Chuan Shi Ruobing Xie Haili Yang Cheng Yang Xu Zhang and Leyu Lin. 2021. Package Recommendation with Intra- and Inter-Package Attention Networks. In SIGIR. ACM 595--604.","DOI":"10.1145\/3404835.3462841"},{"key":"e_1_3_2_1_19_1","unstructured":"Sihang Li Xiang Wang An Zhang Xiangnan He and Tat-Seng Chua. 2022. Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. In ICML."},{"key":"e_1_3_2_1_20_1","unstructured":"Xingchen Li Xiang Wang Xiangnan He Long Chen Jun Xiao and Tat-Seng Chua. 2020. Hierarchical Fashion Graph Network for Personalized Outfit Recommendation. In SIGIR. ACM 159--168."},{"key":"e_1_3_2_1_21_1","volume-title":"Contrastive self-supervised sequential recommendation with robust augmentation. arXiv preprint arXiv:2108.06479","author":"Liu Zhiwei","year":"2021","unstructured":"Zhiwei Liu, Yongjun Chen, Jia Li, Philip S Yu, Julian McAuley, and Caiming Xiong. 2021. Contrastive self-supervised sequential recommendation with robust augmentation. arXiv preprint arXiv:2108.06479 (2021)."},{"key":"e_1_3_2_1_22_1","unstructured":"Lajanugen Logeswaran and Honglak Lee. 2018. An efficient framework for learning sentence representations. In ICLR (Poster) . OpenReview.net."},{"key":"e_1_3_2_1_23_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_24_1","doi-asserted-by":"crossref","unstructured":"Yuqi Qin Pengfei Wang and Chenliang Li. 2021. The World is Binary: Contrastive Learning for Denoising Next Basket Recommendation. In SIGIR. ACM 859--868.","DOI":"10.1145\/3404835.3462836"},{"key":"e_1_3_2_1_25_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_26_1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle Christoph Freudenthaler and Lars Schmidt-Thieme. 2010. Factorizing personalized Markov chains for next-basket recommendation. In WWW. ACM 811--820.","DOI":"10.1145\/1772690.1772773"},{"key":"e_1_3_2_1_27_1","volume-title":"ICML (Proceedings of Machine Learning Research","volume":"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 ICML (Proceedings of Machine Learning Research, Vol. 119). PMLR, 9929--9939."},{"key":"e_1_3_2_1_28_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. ACM 165--174.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Yinwei Wei Xiang Wang Qi Li Liqiang Nie Yan Li Xuanping Li and Tat-Seng Chua. 2021. Contrastive Learning for Cold-Start Recommendation. In ACM Multimedia . ACM 5382--5390.","DOI":"10.1145\/3474085.3475665"},{"key":"e_1_3_2_1_30_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. ACM 726--735.","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_1_31_1","unstructured":"Yingxin Wu Xiang Wang An Zhang Xiangnan He and Tat-Seng Chua. 2022. Discovering Invariant Rationales for Graph Neural Networks. In ICLR ."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Xin Xia Hongzhi Yin Junliang Yu Yingxia Shao and Lizhen Cui. 2021 a. Self-Supervised Graph Co-Training for Session-based Recommendation. In CIKM. ACM 2180--2190.","DOI":"10.1145\/3459637.3482388"},{"key":"e_1_3_2_1_33_1","volume-title":"2021 b. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation","author":"Xia Xin","unstructured":"Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. 2021 b. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. In AAAI. AAAI Press, 4503--4511."},{"key":"e_1_3_2_1_34_1","volume-title":"Contrastive Learning for Sequential Recommendation. arXiv preprint arXiv:2010.14395","author":"Xie Xu","year":"2020","unstructured":"Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Bolin Ding, and Bin Cui. 2020. Contrastive Learning for Sequential Recommendation. arXiv preprint arXiv:2010.14395 (2020)."},{"key":"e_1_3_2_1_35_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. ACM 974--983.","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467340"},{"key":"e_1_3_2_1_37_1","unstructured":"Yifan Zhang Bryan Hooi Dapeng Hu Jian Liang and Jiashi Feng. 2021. Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. In NeurIPS. 29848--29860."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Chang Zhou Jianxin Ma Jianwei Zhang Jingren Zhou and Hongxia Yang. 2021 a. Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems. In KDD. ACM 3985--3995.","DOI":"10.1145\/3447548.3467102"},{"key":"e_1_3_2_1_39_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. S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In CIKM. ACM , 1893--1902."},{"key":"e_1_3_2_1_40_1","volume-title":"2021 b. 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 b. SelfCF: A Simple Framework for Self-supervised Collaborative Filtering. arXiv preprint arXiv:2107.03019 (2021)."}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Washington DC USA","acronym":"KDD '22","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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539229","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539229","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:59:58Z","timestamp":1750186798000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539229"}},"subtitle":["Cross-view Contrastive Learning for Bundle Recommendation"],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":40,"alternative-id":["10.1145\/3534678.3539229","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539229","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}