{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T05:21:27Z","timestamp":1772256087397,"version":"3.50.1"},"reference-count":106,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"crossref","award":["62072304, and 62172277"],"award-info":[{"award-number":["62072304, and 62172277"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003399","name":"Shanghai Municipal Science and Technology Commission","doi-asserted-by":"crossref","award":["21511104700"],"award-info":[{"award-number":["21511104700"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Shanghai East Talents Program"},{"name":"Oceanic Interdisciplinary Program of Shanghai Jiao Tong University","award":["SL2020MS032"],"award-info":[{"award-number":["SL2020MS032"]}]},{"name":"Zhejiang Aoxin Co. Ltd"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2024,5,31]]},"abstract":"<jats:p>Cross-domain recommendation (CDR), which leverages information collected from other domains, has been empirically demonstrated to effectively alleviate data sparsity and cold-start problems encountered in traditional recommendation systems. However, current CDR methods, including those considering time information, do not jointly model the general and current interests within and across domains, which is pivotal for accurately predicting users\u2019 future interactions. In this article, we propose a Contrastive learning-enhanced Multi-View interest learning model (CMVCDR) for cross-domain sequential recommendation. Specifically, we design a static view and a sequential view to model uses\u2019 general interests and current interests, respectively. We divide a user\u2019s general interest representation into a domain-invariant part and a domain-specific part. A cross-domain contrastive learning objective is introduced to impose constraints for optimizing these representations. In the sequential view, we first devise an attention mechanism guided by users\u2019 domain-invariant interest representations to distill cross-domain knowledge pertaining to domain-invariant factors while reducing noise from irrelevant factors. We further design a domain-specific interest-guided temporal information aggregation mechanism to generate users\u2019 current interest representations. Extensive experiments demonstrate the effectiveness of our proposed model compared with state-of-the-art methods.<\/jats:p>","DOI":"10.1145\/3632402","type":"journal-article","created":{"date-parts":[[2023,11,9]],"date-time":"2023-11-09T11:42:46Z","timestamp":1699530166000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Contrastive Multi-view Interest Learning for Cross-domain Sequential Recommendation"],"prefix":"10.1145","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9390-3740","authenticated-orcid":false,"given":"Tianzi","family":"Zang","sequence":"first","affiliation":[{"name":"Nanjing University of Aeronautics and Astronautics, China, and Shanghai Jiao TongUniversity, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-4992","authenticated-orcid":false,"given":"Yanmin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1764-0023","authenticated-orcid":false,"given":"Ruohan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1752-5423","authenticated-orcid":false,"given":"Chunyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8088-607X","authenticated-orcid":false,"given":"Ke","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0207-9643","authenticated-orcid":false,"given":"Jiadi","family":"Yu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]}],"member":"320","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159727"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557262"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531967"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462968"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441826"},{"key":"e_1_3_2_7_2","first-page":"1597","volume-title":"Proceedings of the 37th International Conference on Machine Learning (ICML\u201920)","volume":"119","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 Proceedings of the 37th International Conference on Machine Learning (ICML\u201920), Vol. 119. PMLR, 1597\u20131607."},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512090"},{"key":"e_1_3_2_9_2","first-page":"2605","volume-title":"Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI\u201913)","author":"Cheng Chen","year":"2013","unstructured":"Chen Cheng, Haiqin Yang, Michael R. Lyu, and Irwin King. 2013. Where you like to go next: Successive point-of-interest recommendation. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI\u201913). IJCAI\/AAAI, 2605\u20132611."},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00153"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557266"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482242"},{"key":"e_1_3_2_13_2","volume-title":"International Conference on Machine Learning (ICML\u201922) (Proceedings of Machine Learning Research, Vol. 162)","author":"Fei Hao","year":"2022","unstructured":"Hao Fei, Shengqiong Wu, Yafeng Ren, and Meishan Zhang. 2022. Matching structure for dual learning. In International Conference on Machine Learning (ICML\u201922) (Proceedings of Machine Learning Research, Vol. 162). PMLR, 6373\u20136391."},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.330194"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/342"},{"key":"e_1_3_2_16_2","volume-title":"AISTATS (JMLR Proceedings, Vol. 9)","author":"Gutmann Michael","year":"2010","unstructured":"Michael Gutmann and Aapo Hyv\u00e4rinen. 2010. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. In AISTATS (JMLR Proceedings, Vol. 9). JMLR.org, 297\u2013304."},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0030"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2831682"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271761"},{"key":"e_1_3_2_21_2","volume-title":"4th International Conference on Learning Representations (ICLR\u201916)","author":"Hidasi Bal\u00e1zs","year":"2016","unstructured":"Bal\u00e1zs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2016. Session-based recommendations with recurrent neural networks. In 4th International Conference on Learning Representations (ICLR\u201916)."},{"key":"e_1_3_2_22_2","volume-title":"Advances in Neural Information Processing Systems (NeurIPS\u201920)","author":"Ho Chih-Hui","year":"2020","unstructured":"Chih-Hui Ho and Nuno Vasconcelos. 2020. Contrastive learning with adversarial examples. In Advances in Neural Information Processing Systems (NeurIPS\u201920)."},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.76"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271684"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210017"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00250"},{"key":"e_1_3_2_27_2","article-title":"Contrastive self-supervised learning in recommender systems: A survey","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. ACM Trans. Inf. Syst. (2023).","journal-title":"ACM Trans. Inf. Syst."},{"key":"e_1_3_2_28_2","first-page":"590","volume-title":"ECML PKDD","author":"Jing Mengyuan","year":"2022","unstructured":"Mengyuan Jing, Yanmin Zhu, Tianzi Zang, Jiadi Yu, and Feilong Tang. 2022. Graph contrastive learning with adaptive augmentation for recommendation. In ECML PKDD, Vol. 13713. Springer, 590\u2013605."},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487589"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357914"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.197"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557072"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371786"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467140"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371793"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380036"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412012"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219950"},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583366"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482480"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5945"},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1145\/1458082.1458205"},{"key":"e_1_3_2_45_2","first-page":"5712","volume-title":"Advances in Neural Information Processing Systems (NeurIPS\u201919)","author":"Ma Jianxin","year":"2019","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\u201919). 5712\u20135723."},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1145\/3487331"},{"key":"e_1_3_2_47_2","first-page":"685","volume-title":"Proceedings of the 42nd International Conference on Research and Development in Information Retrieval (SIGIR\u201919)","author":"Ma Muyang","year":"2019","unstructured":"Muyang Ma, Pengjie Ren, Yujie Lin, Zhumin Chen, Jun Ma, and Maarten de Rijke. 2019. \\(\\pi\\) -Net: A parallel information-sharing network for shared-account cross-domain sequential recommendations. In Proceedings of the 42nd International Conference on Research and Development in Information Retrieval (SIGIR\u201919). ACM, 685\u2013694."},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539229"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/343"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412728"},{"key":"e_1_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.5555\/3304222.3304301"},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5350"},{"key":"e_1_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.191"},{"key":"e_1_3_2_54_2","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498433"},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109896"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401111"},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772773"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401969"},{"key":"e_1_3_2_59_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_61_2","volume-title":"The 10th International Conference on Learning Representations (ICLR\u201922)","author":"Tsai Yao-Hung Hubert","year":"2022","unstructured":"Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2022. Conditional contrastive learning with kernel. In The 10th International Conference on Learning Representations (ICLR\u201922). OpenReview.net."},{"issue":"1","key":"e_1_3_2_62_2","first-page":"3221","article-title":"Accelerating t-SNE using tree-based algorithms","volume":"15","author":"Maaten Laurens van der","year":"2014","unstructured":"Laurens van der Maaten. 2014. Accelerating t-SNE using tree-based algorithms. J. Mach. Learn. Res. 15, 1 (2014), 3221\u20133245.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_63_2","first-page":"5998","volume-title":"Advances in Neural Information Processing Systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 5998\u20136008."},{"key":"e_1_3_2_64_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557317"},{"key":"e_1_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401134"},{"key":"e_1_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482137"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401137"},{"key":"e_1_3_2_68_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91452-7_11"},{"key":"e_1_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00304"},{"key":"e_1_3_2_70_2","first-page":"5382","volume-title":"MM","author":"Wei Yinwei","year":"2021","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 MM. ACM, 5382\u20135390."},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_72_2","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412258"},{"key":"e_1_3_2_73_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.146"},{"key":"e_1_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"e_1_3_2_75_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.269"},{"key":"e_1_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.176"},{"key":"e_1_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539125"},{"key":"e_1_3_2_78_2","article-title":"Contrastive pre-training for sequential recommendation","volume":"2010","author":"Xie Xu","year":"2020","unstructured":"Xu Xie, Fei Sun, Zhaoyang Liu, Jinyang Gao, Bolin Ding, and Bin Cui. 2020. Contrastive pre-training for sequential recommendation. CoRR abs\/2010.14395 (2020).","journal-title":"CoRR"},{"key":"e_1_3_2_79_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"e_1_3_2_80_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401147"},{"key":"e_1_3_2_81_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/547"},{"key":"e_1_3_2_82_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313408"},{"key":"e_1_3_2_83_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358113"},{"key":"e_1_3_2_84_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532009"},{"key":"e_1_3_2_85_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481952"},{"key":"e_1_3_2_86_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/546"},{"key":"e_1_3_2_87_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467340"},{"key":"e_1_3_2_88_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449844"},{"key":"e_1_3_2_89_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531937"},{"key":"e_1_3_2_90_2","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290975"},{"key":"e_1_3_2_91_2","doi-asserted-by":"publisher","DOI":"10.1145\/3548455"},{"key":"e_1_3_2_92_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557289"},{"key":"e_1_3_2_93_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-30672-3_14"},{"key":"e_1_3_2_94_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00098"},{"key":"e_1_3_2_95_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/355"},{"key":"e_1_3_2_96_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/333"},{"key":"e_1_3_2_97_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358166"},{"key":"e_1_3_2_98_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401169"},{"key":"e_1_3_2_99_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20359"},{"key":"e_1_3_2_100_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91452-7_10"},{"key":"e_1_3_2_101_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548072"},{"key":"e_1_3_2_102_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512098"},{"key":"e_1_3_2_103_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449788"},{"key":"e_1_3_2_104_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411954"},{"key":"e_1_3_2_105_2","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583286"},{"key":"e_1_3_2_106_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357992"},{"key":"e_1_3_2_107_2","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498392"}],"container-title":["ACM Transactions on Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632402","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3632402","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:45:43Z","timestamp":1750178743000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3632402"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,29]]},"references-count":106,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,5,31]]}},"alternative-id":["10.1145\/3632402"],"URL":"https:\/\/doi.org\/10.1145\/3632402","relation":{},"ISSN":["1046-8188","1558-2868"],"issn-type":[{"value":"1046-8188","type":"print"},{"value":"1558-2868","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,29]]},"assertion":[{"value":"2022-11-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-11-05","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-12-29","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}