{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T02:36:14Z","timestamp":1775010974438,"version":"3.50.1"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031001253","type":"print"},{"value":"9783031001260","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-00126-0_22","type":"book-chapter","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T18:07:55Z","timestamp":1650996475000},"page":"298-305","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Deep Graph Mutual Learning for\u00a0Cross-domain Recommendation"],"prefix":"10.1007","author":[{"given":"Yifan","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yongkang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Shuai","family":"Li","sequence":"additional","affiliation":[]},{"given":"Weiping","family":"Song","sequence":"additional","affiliation":[]},{"given":"Jiangke","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Shan","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Bing","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Xunliang","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Sheng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Ming","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"key":"22_CR1","doi-asserted-by":"crossref","unstructured":"Fan, S., et al.: Metapath-guided heterogeneous graph neural network for intent recommendation. In: SIGKDD, pp. 2478\u20132486 (2019)","DOI":"10.1145\/3292500.3330673"},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"He, R., McAuley, J.J.: Ups and downs: modeling the visual evolution of fashion trends with one-class collaborative filtering. In: WWW, pp. 507\u2013517 (2016)","DOI":"10.1145\/2872427.2883037"},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"He, X., Deng, K., Wang, X., Li, Y., Zhang, Y., Wang, M.: Lightgcn: simplifying and powering graph convolution network for recommendation. In: SIGIR, pp. 639\u2013648 (2020)","DOI":"10.1145\/3397271.3401063"},{"key":"22_CR4","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., Nie, L., Hu, X., Chua, T.S.: Neural collaborative filtering. In: WWW, pp. 173\u2013182 (2017)","DOI":"10.1145\/3038912.3052569"},{"key":"22_CR5","unstructured":"Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)"},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Hu, G., Zhang, Y., Yang, Q.: Conet: collaborative cross networks for cross-domain recommendation. In: CIKM, pp. 667\u2013676 (2018)","DOI":"10.1145\/3269206.3271684"},{"key":"22_CR7","unstructured":"Li, B., Yang, Q., Xue, X.: Can movies and books collaborate? cross-domain collaborative filtering for sparsity reduction. In: IJCAI (2009)"},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Li, P., Tuzhilin, A.: DDTCDR: deep dual transfer cross domain recommendation. In: WSDM, pp. 331\u2013339 (2020)","DOI":"10.1145\/3336191.3371793"},{"key":"22_CR9","doi-asserted-by":"crossref","unstructured":"Liu, M., Li, J., Li, G., Pan, P.: Cross domain recommendation via bi-directional transfer graph collaborative filtering networks. In: CIKM, pp. 885\u2013894 (2020)","DOI":"10.1145\/3340531.3412012"},{"key":"22_CR10","doi-asserted-by":"crossref","unstructured":"Loni, B., Shi, Y., Larson, M., Hanjalic, A.: Cross-domain collaborative filtering with factorization machines. In: ECIR, pp. 656\u2013661 (2014)","DOI":"10.1007\/978-3-319-06028-6_72"},{"key":"22_CR11","unstructured":"Rendle, S., Freudenthaler, C., Gantner, Z., Schmidt-Thieme, L.: BPR: Bayesian personalized ranking from implicit feedback. In: UAI, pp. 452\u2013461 (2009)"},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Singh, A.P., Gordon, G.J.: Relational learning via collective matrix factorization. In: SIGKDD, pp. 650\u2013658 (2008)","DOI":"10.21236\/ADA486804"},{"key":"22_CR13","doi-asserted-by":"crossref","unstructured":"Wang, X., He, X., Wang, M., Feng, F., Chua, T.S.: Neural graph collaborative filtering. In: SIGIR, pp. 165\u2013174 (2019)","DOI":"10.1145\/3331184.3331267"},{"key":"22_CR14","doi-asserted-by":"crossref","unstructured":"Wang, Y., Tang, S., Lei, Y., Song, W., Wang, S., Zhang, M.: Disenhan: disentangled heterogeneous graph attention network for recommendation. In: CIKM, pp. 1605\u20131614 (2020)","DOI":"10.1145\/3340531.3411996"},{"key":"22_CR15","doi-asserted-by":"crossref","unstructured":"Ying, R., He, R., Chen, K., Eksombatchai, P., Hamilton, W.L., Leskovec, J.: Graph convolutional neural networks for web-scale recommender systems. In: SIGKDD, pp. 974\u2013983 (2018)","DOI":"10.1145\/3219819.3219890"},{"key":"22_CR16","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Xiang, T., Hospedales, T.M., Lu, H.: Deep mutual learning. In: CVPR, pp. 4320\u20134328 (2018)","DOI":"10.1109\/CVPR.2018.00454"},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Xu, X., Zhou, H., Zhang, Y.: Distilling structured knowledge into embeddings for explainable and accurate recommendation. In: WSDM, pp. 735\u2013743 (2020)","DOI":"10.1145\/3336191.3371790"},{"key":"22_CR18","doi-asserted-by":"crossref","unstructured":"Zhao, C., Li, C., Fu, C.: Cross-domain recommendation via preference propagation graphnet. In: CIKM, pp. 2165\u20132168 (2019)","DOI":"10.1145\/3357384.3358166"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, J., et al.: Ensembled CTR prediction via knowledge distillation. In: CIKM, pp. 2941\u20132958 (2020)","DOI":"10.1145\/3340531.3412704"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-00126-0_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T18:12:15Z","timestamp":1650996735000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-00126-0_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031001253","9783031001260"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-00126-0_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"8 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.dasfaa2022.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"543","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"76","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was originally planned to take place in Hyberabad, India. 24 other papers are included in the volume.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}