{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T02:35:32Z","timestamp":1783737332994,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSFC","award":["62032003"],"award-info":[{"award-number":["62032003"]}]},{"name":"National Key R&D Program of China","award":["2022YFB3104200"],"award-info":[{"award-number":["2022YFB3104200"]}]},{"name":"research grant","award":["SH-2024JK29"],"award-info":[{"award-number":["SH-2024JK29"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671799","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"2745-2754","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Mitigating Negative Transfer in Cross-Domain Recommendation via Knowledge Transferability Enhancement"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7725-2497","authenticated-orcid":false,"given":"Zijian","family":"Song","sequence":"first","affiliation":[{"name":"School of CS, Peking University & National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3015-8596","authenticated-orcid":false,"given":"Wenhan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of CS, Peking University & National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6940-8303","authenticated-orcid":false,"given":"Lifang","family":"Deng","sequence":"additional","affiliation":[{"name":"Lazada Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3404-1559","authenticated-orcid":false,"given":"Jiandong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Lazada Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7286-319X","authenticated-orcid":false,"given":"Zhihua","family":"Wu","sequence":"additional","affiliation":[{"name":"Lazada Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0136-6082","authenticated-orcid":false,"given":"Kaigui","family":"Bian","sequence":"additional","affiliation":[{"name":"School of CS, Peking University & National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1681-4677","authenticated-orcid":false,"given":"Bin","family":"Cui","sequence":"additional","affiliation":[{"name":"School of CS, Peking University & National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00997"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2019.2923315"},{"key":"e_1_3_2_2_3_1","volume-title":"A theory of learning from different domains. Machine learning","author":"Ben-David Shai","year":"2010","unstructured":"Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010. A theory of learning from different domains. Machine learning, Vol. 79 (2010), 151--175."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531967"},{"key":"e_1_3_2_2_5_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_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/2354409.2355024"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/2188385.2188410"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3185101"},{"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","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271684"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570379"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371793"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41019-023-00215-w"},{"key":"e_1_3_2_2_16_1","volume-title":"Improving EEG-based emotion classification using conditional transfer learning. Frontiers in human neuroscience","author":"Lin Yuan-Pin","year":"2017","unstructured":"Yuan-Pin Lin and Tzyy-Ping Jung. 2017. Improving EEG-based emotion classification using conditional transfer learning. Frontiers in human neuroscience, Vol. 11 (2017), 334."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412012"},{"key":"e_1_3_2_2_18_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_2_19_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1018"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2900467"},{"key":"e_1_3_2_2_21_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_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67658-2_23"},{"key":"e_1_3_2_2_23_1","volume-title":"NIPS 2005 workshop on transfer learning","volume":"898","author":"Rosenstein Michael T","year":"2005","unstructured":"Michael T Rosenstein, Zvika Marx, Leslie Pack Kaelbling, and Thomas G Dietterich. 2005. To transfer or not to transfer. In NIPS 2005 workshop on transfer learning, Vol. 898."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3404-y"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-10928-8_47"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01155"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2014.6974353"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3274-6"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41019-023-00226-7"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482429"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106132"},{"key":"e_1_3_2_2_35_1","first-page":"17","article-title":"Deepapf: Deep attentive probabilistic factorization for multi-site video recommendation","volume":"2","author":"Yan Huan","year":"2019","unstructured":"Huan Yan, Xiangning Chen, Chen Gao, Yong Li, and Depeng Jin. 2019. Deepapf: Deep attentive probabilistic factorization for multi-site video recommendation. TC, Vol. 2, 130 (2019), 17--883.","journal-title":"TC"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462928"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3548455"},{"key":"e_1_3_2_2_38_1","volume-title":"A survey on negative transfer","author":"Zhang Wen","year":"2022","unstructured":"Wen Zhang, Lingfei Deng, Lei Zhang, and Dongrui Wu. 2022. A survey on negative transfer. IEEE\/CAA Journal of Automatica Sinica (2022)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2020.2985996"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358166"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498381"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357992"},{"key":"e_1_3_2_2_43_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_44_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. 2021. Cross-domain recommendation: challenges, progress, and prospects. arXiv preprint arXiv:2103.01696 (2021)."},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3104873"}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671799","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671799","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:14Z","timestamp":1750291454000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":45,"alternative-id":["10.1145\/3637528.3671799","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671799","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}