{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:59:51Z","timestamp":1774367991465,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":41,"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"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,2,27]]},"DOI":"10.1145\/3539597.3570379","type":"proceedings-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T23:27:00Z","timestamp":1677108420000},"page":"366-374","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":49,"title":["One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7477-7945","authenticated-orcid":false,"given":"Chenglin","family":"Li","sequence":"first","affiliation":[{"name":"University of Alberta, Edmonton, AB, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8010-3434","authenticated-orcid":false,"given":"Yuanzhen","family":"Xie","sequence":"additional","affiliation":[{"name":"Tencent, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9774-1590","authenticated-orcid":false,"given":"Chenyun","family":"Yu","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1078-537X","authenticated-orcid":false,"given":"Bo","family":"Hu","sequence":"additional","affiliation":[{"name":"Tencent, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2305-7179","authenticated-orcid":false,"given":"Zang","family":"Li","sequence":"additional","affiliation":[{"name":"Tencent, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1165-1936","authenticated-orcid":false,"given":"Guoqiang","family":"Shu","sequence":"additional","affiliation":[{"name":"Tencent, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6539-1231","authenticated-orcid":false,"given":"Xiaohu","family":"Qie","sequence":"additional","affiliation":[{"name":"Tencent, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5250-7327","authenticated-orcid":false,"given":"Di","family":"Niu","sequence":"additional","affiliation":[{"name":"University of Alberta, Edmonton, AB, Canada"}]}],"member":"320","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Paszke Adam Gross Sam Chintala Soumith and Chanan Gregory. 2017. Pytorch:Tensors and dynamic neural networks in python with strong gpu acceleration. https:\/\/pytorch.org\/."},{"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","unstructured":"Qiang Cui Tao Wei Yafeng Zhang and Qing Zhang. 2020. HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation.. In ORSUM@ RecSys."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741667"},{"key":"e_1_3_2_2_5_1","volume-title":"Artificial neural networks (the multilayer perceptron)-a review of applications in the atmospheric sciences. Atmospheric environment","author":"Gardner Matt W","year":"1998","unstructured":"Matt W Gardner and SR Dorling. 1998. Artificial neural networks (the multilayer perceptron)-a review of applications in the atmospheric sciences. Atmospheric environment, Vol. 32, 14--15 (1998), 2627--2636."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_2_7_1","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems. 1025--1035","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Proceedings of the 31st International Conference on Neural Information Processing Systems. 1025--1035."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_10_1","volume-title":"ACM Transactions on Information Systems (TOIS)","volume":"20","author":"Jaana Kalervo","year":"2002","unstructured":"Kalervo J\"arvelin and Jaana Kek\"al\"ainen. 2002. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS), Vol. 20, 4 (2002), 422--446."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-15719-7_3"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357914"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291019"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401078"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498388"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371793"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3074395"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380036"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412012"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1458082.1458205"},{"key":"e_1_3_2_2_21_1","first-page":"2464","article-title":"Cross-Domain Recommendation: An Embedding and Mapping Approach","volume":"17","author":"Man Tong","year":"2017","unstructured":"Tong Man, Huawei Shen, Xiaolong Jin, and Xueqi Cheng. 2017. Cross-Domain Recommendation: An Embedding and Mapping Approach.. In IJCAI, Vol. 17. 2464--2470.","journal-title":"IJCAI"},{"key":"e_1_3_2_2_22_1","volume-title":"Proceedings of the first instructional conference on machine learning","volume":"242","author":"Juan","unstructured":"Juan Ramos et al. 2003. Using tf-idf to determine word relevance in document queries. In Proceedings of the first instructional conference on machine learning, Vol. 242. Citeseer, 29--48."},{"key":"e_1_3_2_2_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_2_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.02.024"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401969"},{"key":"e_1_3_2_2_26_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_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290973"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2926078"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401156"},{"key":"e_1_3_2_2_31_1","volume-title":"DARec: Deep domain adaptation for cross-domain recommendation via transferring rating patterns. arXiv preprint arXiv:1905.10760","author":"Yuan Feng","year":"2019","unstructured":"Feng Yuan, Lina Yao, and Boualem Benatallah. 2019. DARec: Deep domain adaptation for cross-domain recommendation via transferring rating patterns. arXiv preprint arXiv:1905.10760 (2019)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462884"},{"key":"e_1_3_2_2_33_1","volume-title":"Overcoming negative transfer: A survey. arXiv preprint arXiv:2009.00909","author":"Zhang Wen","year":"2020","unstructured":"Wen Zhang, Lingfei Deng, Lei Zhang, and Dongrui Wu. 2020. Overcoming negative transfer: A survey. arXiv preprint arXiv:2009.00909 (2020)."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401169"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498381"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357992"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Feng Zhu Yan Wang Chaochao Chen Guanfeng Liu and Xiaolin Zheng. 2020. A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation.. In IJCAI. 3001--3008.","DOI":"10.24963\/ijcai.2020\/415"},{"key":"e_1_3_2_2_38_1","volume-title":"Cross-domain recommendation: challenges, progress, and prospects. arXiv preprint arXiv:2103.01696","author":"Zhu Feng","year":"2021","unstructured":"Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, and Guanfeng Liu. 2021a. Cross-domain recommendation: challenges, progress, and prospects. arXiv preprint arXiv:2103.01696 (2021)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3104873"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498392"},{"key":"e_1_3_2_2_41_1","volume-title":"Cross-domain novelty seeking trait mining for sequential recommendation. arXiv preprint arXiv:1803.01542","author":"Zhuang Fuzhen","year":"2018","unstructured":"Fuzhen Zhuang, Yingmin Zhou, Fuzheng Zhang, Xiang Ao, Xing Xie, and Qing He. 2018. Cross-domain novelty seeking trait mining for sequential recommendation. arXiv preprint arXiv:1803.01542 (2018)."}],"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\/3539597.3570379","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3539597.3570379","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\/3539597.3570379"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,27]]},"references-count":41,"alternative-id":["10.1145\/3539597.3570379","10.1145\/3539597"],"URL":"https:\/\/doi.org\/10.1145\/3539597.3570379","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"}}]}}