{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T15:36:17Z","timestamp":1772206577560,"version":"3.50.1"},"reference-count":44,"publisher":"Informa UK Limited","issue":"1","license":[{"start":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T00:00:00Z","timestamp":1695945600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076006"],"award-info":[{"award-number":["62076006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University Key Scientific Research Project of Anhui Province","award":["2022AH050821"],"award-info":[{"award-number":["2022AH050821"]}]}],"content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Connection Science"],"published-print":{"date-parts":[[2023,12,31]]},"DOI":"10.1080\/09540091.2023.2263664","type":"journal-article","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T18:39:16Z","timestamp":1696012756000},"update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":5,"title":["Neighbor interaction-based personalised transfer for cross-domain recommendation"],"prefix":"10.1080","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3966-2031","authenticated-orcid":false,"given":"Kelei","family":"Sun","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengqi","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaping","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Anhui University of Science &amp; Technology, Huainan, People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2023,9,29]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2019.01.012"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511711"},{"key":"e_1_3_2_4_1","doi-asserted-by":"crossref","unstructured":"He X. Liao L. Zhang H. Nie L. Hu X. & Chua T. S. (2017). Neural collaborative filtering. In Proceedings of the 26th international conference on world wide web (pp. 173\u2013182). ACM.","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.071"},{"issue":"9","key":"e_1_3_2_6_1","first-page":"5149","article-title":"Meta-learning in neural networks: A survey","volume":"44","author":"Hospedales T.","year":"2021","unstructured":"Hospedales, T., Antoniou, A., Micaelli, P., & Storkey, A. (2021). Meta-learning in neural networks: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9), 5149\u20135169.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_8_1","doi-asserted-by":"crossref","unstructured":"Kang S. Hwang J. Lee D. & Yu H. (2019). Semi-supervised learning for cross-domain recommendation to cold-start users. In Proceedings of the 28th ACM international conference on information and knowledge management (pp. 1563\u20131572). ACM.","DOI":"10.1145\/3357384.3357914"},{"key":"e_1_3_2_9_1","doi-asserted-by":"crossref","unstructured":"Kang W. C. & McAuley J. (2018 November). Self-attentive sequential recommendation. In 2018 IEEE international conference on data mining (ICDM) (pp. 197\u2013206). IEEE.","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3038670"},{"key":"e_1_3_2_11_1","doi-asserted-by":"crossref","unstructured":"Li P. & Tuzhilin A. (2020). Ddtcdr: Deep dual transfer cross domain recommendation. In Proceedings of the 13th international conference on web search and data mining (pp. 331\u2013339). ACM.","DOI":"10.1145\/3336191.3371793"},{"issue":"1","key":"e_1_3_2_12_1","first-page":"321","article-title":"Dual metric learning for effective and efficient cross-domain recommendations","volume":"35","author":"Li P.","year":"2021","unstructured":"Li, P., & Tuzhilin, A. (2021). Dual metric learning for effective and efficient cross-domain recommendations. IEEE Transactions on Knowledge and Data Engineering, 35(1), 321\u2013334.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"4","key":"e_1_3_2_13_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3446427","article-title":"Seamlessly unifying attributes and items: Conversational recommendation for cold-start users","volume":"39","author":"Li S.","year":"2021","unstructured":"Li, S., Lei, W., Wu, Q., He, X., Jiang, P., & Chua, T. S. (2021). Seamlessly unifying attributes and items: Conversational recommendation for cold-start users. ACM Transactions on Information Systems (TOIS), 39(4), 1\u201329.","journal-title":"ACM Transactions on Information Systems (TOIS)"},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.1996537"},{"key":"e_1_3_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.05.114"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116591"},{"key":"e_1_3_2_17_1","doi-asserted-by":"crossref","unstructured":"Lian J. Zhang F. Xie X. & Sun G. (2017 April). CCCFNet: A content-boosted collaborative filtering neural network for cross domain recommender systems. In Proceedings of the 26th international conference on World Wide Web companion (pp. 817\u2013818). ACM.","DOI":"10.1145\/3041021.3054207"},{"key":"e_1_3_2_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.02.009"},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355394"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.12.015"},{"key":"e_1_3_2_21_1","doi-asserted-by":"crossref","unstructured":"Ma H. Yang H. Lyu M. R. & King I. (2008). Sorec: Social recommendation using probabilistic matrix factorization. In Proceedings of the 17th ACM conference on Information and knowledge management (pp. 931\u2013940). ACM.","DOI":"10.1145\/1458082.1458205"},{"key":"e_1_3_2_22_1","doi-asserted-by":"crossref","unstructured":"Man T. Shen H. Jin X. & Cheng X. (2017). Cross-domain recommendation: An embedding and mapping approach. In Proceedings of the 26th international joint conference on artificial intelligence (Vol. 17 pp. 2464\u20132470). Morgan Kaufmann.","DOI":"10.24963\/ijcai.2017\/343"},{"key":"e_1_3_2_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113248"},{"key":"e_1_3_2_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.02.024"},{"key":"e_1_3_2_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106817"},{"key":"e_1_3_2_26_1","doi-asserted-by":"crossref","unstructured":"Singh A. P. & Gordon G. J. (2008). Relational learning via collective matrix factorization. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 650\u2013658). ACM.","DOI":"10.1145\/1401890.1401969"},{"key":"e_1_3_2_27_1","unstructured":"Snell J. Swersky K. & Zemel R. (2017). Prototypical networks for few-shot learning. In Advances in neural information processing systems (pp. 4080\u20134090). ACM."},{"key":"e_1_3_2_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.04.078"},{"key":"e_1_3_2_29_1","unstructured":"Vaswani A. Shazeer N. Parmar N. Uszkoreit J. Jones L. Gomez A. N. Kaiser \u0141. & Polosukhin I. (2017). Attention is all you need. In Advances in neural information processing systems (pp. 5998\u20136008). ACM."},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2022.2136141"},{"key":"e_1_3_2_31_1","doi-asserted-by":"crossref","unstructured":"Wang T. Zhuang F. Zhang Z. Wang D. Zhou J. & He Q. (2021). Low-dimensional alignment for cross-domain recommendation. In Proceedings of the 30th ACM international conference on information & knowledge management (pp. 3508\u20133512). ACM.","DOI":"10.1145\/3459637.3482137"},{"key":"e_1_3_2_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.08.120"},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.10.066"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.106"},{"key":"e_1_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2020.1841110"},{"key":"e_1_3_2_36_1","doi-asserted-by":"crossref","unstructured":"Yu R. Gong Y. He X. Zhu Y. Liu Q. Ou W. & An B. (2021). Personalized adaptive meta learning for cold-start user preference prediction. In Proceedings of the AAAI conference on artificial intelligence (Vol. 35 No. 12 pp. 10772\u201310780). AAAI Press.","DOI":"10.1609\/aaai.v35i12.17287"},{"key":"e_1_3_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3548455"},{"key":"e_1_3_2_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2017.10.002"},{"key":"e_1_3_2_39_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJCSE.2022.126251"},{"key":"e_1_3_2_40_1","doi-asserted-by":"crossref","unstructured":"Zhao C. Li C. Xiao R. Deng H. & Sun A. (2020). CATN: Cross-domain recommendation for cold-start users via aspect transfer network. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval (pp. 229\u2013238). ACM.","DOI":"10.1145\/3397271.3401169"},{"key":"e_1_3_2_41_1","doi-asserted-by":"crossref","unstructured":"Zheng Y. Liu S. Li Z. & Wu S. (2021 May). Cold-start sequential recommendation via meta learner. In Proceedings of the AAAI conference on artificial intelligence (Vol. 35 No. 5 pp. 4706\u20134713). AAAI Press.","DOI":"10.1609\/aaai.v35i5.16601"},{"key":"e_1_3_2_42_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJCSE.2019.101897"},{"key":"e_1_3_2_43_1","doi-asserted-by":"crossref","unstructured":"Zhu F. Wang Y. Chen C. Liu G. Orgun M. & Wu J. (2018). A deep framework for cross-domain and cross-system recommendations. In Proceedings of the 27th international joint conference on artificial intelligence (pp. 3711\u20133717). Morgan Kaufmann.","DOI":"10.24963\/ijcai.2018\/516"},{"key":"e_1_3_2_44_1","doi-asserted-by":"crossref","unstructured":"Zhu Y. Ge K. Zhuang F. Xie R. & Xi D. (2021). Transfer-meta framework for cross-domain recommendation to cold-start users. In Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval (pp. 1813\u20131817). ACM.","DOI":"10.1145\/3404835.3463010"},{"key":"e_1_3_2_45_1","doi-asserted-by":"crossref","unstructured":"Zhu Y. Tang Z. Liu Y. Zhuang F. & Xie R. (2022). Personalized transfer of user preferences for cross-domain recommendation. In Proceedings of the fifteenth ACM international conference on web search and data mining (pp. 1507\u20131515). ACM.","DOI":"10.1145\/3488560.3498392"}],"container-title":["Connection Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/09540091.2023.2263664","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T07:58:11Z","timestamp":1703750291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/09540091.2023.2263664"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,29]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,12,31]]}},"alternative-id":["10.1080\/09540091.2023.2263664"],"URL":"https:\/\/doi.org\/10.1080\/09540091.2023.2263664","relation":{},"ISSN":["0954-0091","1360-0494"],"issn-type":[{"value":"0954-0091","type":"print"},{"value":"1360-0494","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,29]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ccos20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=ccos20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2023-04-27","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-09-20","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-09-29","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2263664"}}