{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T01:45:05Z","timestamp":1787017505265,"version":"build-2736575974"},"reference-count":69,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2023,10,16]],"date-time":"2023-10-16T00:00:00Z","timestamp":1697414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Science Foundation","award":["IIS-1849816, IIS-2142827, IIS-2146761, IIS-2234058"],"award-info":[{"award-number":["IIS-1849816, IIS-2142827, IIS-2146761, IIS-2234058"]}]},{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"crossref","award":["N00014-22-1-2507"],"award-info":[{"award-number":["N00014-22-1-2507"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2024,1,31]]},"abstract":"<jats:p>\n                    Graph neural networks have been widely used for learning representations of nodes for many downstream tasks on graph data. Existing models were designed for the nodes on a single graph, which would not be able to utilize information across multiple graphs. The real world does have multiple graphs where the nodes are often\n                    <jats:italic>partially aligned<\/jats:italic>\n                    . For examples, knowledge graphs share a number of named entities though they may have different relation schema; collaboration networks on publications and awarded projects share some researcher nodes who are authors and investigators, respectively; people use multiple web services, shopping, tweeting, rating movies, and some may register the same e-mail account across the platforms. In this article, we propose partially aligned graph convolutional networks to learn node representations across the models. We provide multiple methods such as model sharing, regularization, and alignment reconstruction, as well as theoretical analysis to\n                    <jats:italic>positively<\/jats:italic>\n                    transfer knowledge across the set of partially aligned nodes. Extensive experiments on real-world knowledge graphs, collaboration networks, and bipartite rating graphs show the superior performance of our proposed methods on relation classification, link prediction, and item recommendation.\n                  <\/jats:p>","DOI":"10.1145\/3617376","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T10:40:26Z","timestamp":1692787226000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Transfer Learning across Graph Convolutional Networks: Methods, Theory, and Applications"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3009-519X","authenticated-orcid":false,"given":"Meng","family":"Jiang","sequence":"first","affiliation":[{"name":"University of Notre Dame, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,10,16]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"2787","article-title":"Translating embeddings for modeling multi-relational data","author":"Bordes Antoine","year":"2013","unstructured":"Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. InProceedings of the 26th International Conference on Neural Information Processing Systems. 2787\u20132795.","journal-title":"Proceedings of the 26th International Conference on Neural Information Processing Systems"},{"key":"e_1_3_2_3_2","first-page":"1548","article-title":"Graph regularized nonnegative matrix factorization for data representation","author":"Cai Deng","year":"2010","unstructured":"Deng Cai, Xiaofei He, Jiawei Han, and Thomas S. Huang. 2010. Graph regularized nonnegative matrix factorization for data representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 8 (2010), 1548\u20131560.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2982878"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132904"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2849727"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098036"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.5555\/3367243.3367352"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.01.074"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380297"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209987"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0234978"},{"key":"e_1_3_2_14_2","first-page":"1024","volume-title":"Proceedings of the International Conference on Neural Information Processing Systems","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Proceedings of the International Conference on Neural Information Processing Systems. 1024\u20131034."},{"key":"e_1_3_2_15_2","unstructured":"William L. Hamilton Rex Ying and Jure Leskovec. 2017. Representation learning on graphs: Methods and applications. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 40 3 (2017) 52\u201374."},{"key":"e_1_3_2_16_2","unstructured":"Chaoyang He Tian Xie Yu Rong Wenbing Huang Yanfang Li Junzhou Huang Xiang Ren and Cyrus Shahabi. 2019. Bipartite graph neural networks for efficient node representation learning. arXiv:1906.11994. Retrieved from https:\/\/arxiv.org\/abs\/1906.11994"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403237"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"e_1_3_2_20_2","first-page":"770","volume-title":"Proceedings of the Asian Conference on Computer Vision","author":"Huang Zhiwu","year":"2012","unstructured":"Zhiwu Huang, Shiguang Shan, Haihong Zhang, Shihong Lao, and Xilin Chen. 2012. Cross-view graph embedding. In Proceedings of the Asian Conference on Computer Vision. Springer, 770\u2013781."},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939815"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467282"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10001"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3501808"},{"key":"e_1_3_2_25_2","unstructured":"Thomas N. Kipf and Max Welling. 2016. Variational graph auto-encoders. In the Bayesian Deep Learning Workshop joint with NIPS 2016 . Preprint: arXiv:1611.07308. Retrieved from https:\/\/arxiv.org\/abs\/1611.07308"},{"key":"e_1_3_2_26_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Kipf Thomas N.","year":"2017","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505531"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.5555\/3367243.3367438"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00149"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539347"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401252"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272010"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403373"},{"key":"e_1_3_2_34_2","unstructured":"Pasin Manurangsi and Daniel Reichman. 2018. The computational complexity of training relu (s). arXiv:1810.04207. Retrieved from https:\/\/arxiv.org\/abs\/1810.04207"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974973.69"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186128"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10314"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411924"},{"key":"e_1_3_2_39_2","article-title":"Beta embeddings for multi-hop logical reasoning in knowledge graphs","author":"Ren Hongyu","year":"2020","unstructured":"Hongyu Ren and Jure Leskovec. 2020. Beta embeddings for multi-hop logical reasoning in knowledge graphs. In Proceedings of the 34th International Conference on Neural Information Processing Systems.","journal-title":"Proceedings of the 34th International Conference on Neural Information Processing Systems"},{"key":"e_1_3_2_40_2","first-page":"15347","volume-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems","author":"Sadeghian Ali","year":"2019","unstructured":"Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, and Daisy Zhe Wang. 2019. DRUM: End-to-end differentiable rule mining on knowledge graphs. In Proceedings of the 33rd International Conference on Neural Information Processing Systems. 15347\u201315357."},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_42_2","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Trouillon Th\u00e9o","year":"2016","unstructured":"Th\u00e9o Trouillon, Johannes Welbl, Sebastian Riedel, \u00c9ric Gaussier, and Guillaume Bouchard. 2016. Complex embeddings for simple link prediction. In Proceedings of the International Conference on Machine Learning."},{"key":"e_1_3_2_43_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Veli\u010dkovi\u0107 Petar","year":"2017","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. In Proceedings of the International Conference on Learning Representations."},{"issue":"5","key":"e_1_3_2_44_2","doi-asserted-by":"crossref","first-page":"1669","DOI":"10.1109\/TCBB.2017.2740381","article-title":"Multiple network alignment via multiMAGNA++","volume":"15","author":"Vijayan Vipin","year":"2017","unstructured":"Vipin Vijayan and Tijana Milenkovi\u0107. 2017. Multiple network alignment via multiMAGNA++. IEEE\/ACM Transactions on Computational Biology and Bioinformatics 15, 5 (2017), 1669\u20131682.","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403308"},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.553"},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975673.78"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313562"},{"key":"e_1_3_2_51_2","volume-title":"Proceedings of the International Conference on Learning Representations","author":"Wu Sen","year":"2019","unstructured":"Sen Wu, Hongyang R. Zhang, and Christopher R\u00e9. 2019. Understanding and improving information transfer in multi-task learning. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_53_2","first-page":"35","article-title":"Multi-task learning for classification with dirichlet process priors","volume":"8","author":"Xue Ya","year":"2007","unstructured":"Ya Xue, Xuejun Liao, Lawrence Carin, and Balaji Krishnapuram. 2007. Multi-task learning for classification with dirichlet process priors. Journal of Machine Learning Research 8, Jan (2007), 35\u201363.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_54_2","unstructured":"Bishan Yang Wen-tau Yih Xiaodong He Jianfeng Gao and Li Deng. 2015. Embedding entities and relations for learning and inference in knowledge bases. In International Conference on Learning Represetnations (ICLR\u201915) . https:\/\/iclr.cc\/archive\/www\/doku.php%3Fid=iclr2015:main.html"},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3026079"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.640"},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.5555\/3367471.3367616"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_59_2","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/754"},{"key":"e_1_3_2_61_2","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3454533"},{"key":"e_1_3_2_62_2","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939766"},{"key":"e_1_3_2_63_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313484"},{"key":"e_1_3_2_64_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.160"},{"key":"e_1_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291014"},{"key":"e_1_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1144"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2981333"},{"key":"e_1_3_2_68_2","unstructured":"Tong Zhao Gang Liu Stephan G\u00fcnnemann and Meng Jiang. 2022. Graph data augmentation for graph machine learning: A survey. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 47 2 (2022) 140\u2013165."},{"key":"e_1_3_2_69_2","first-page":"26911","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Zhao Tong","year":"2022","unstructured":"Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, and Meng Jiang. 2022. Learning from counterfactual links for link prediction. In Proceedings of the International Conference on Machine Learning. PMLR, 26911\u201326926."},{"key":"e_1_3_2_70_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17315"}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3617376","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3617376","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T12:45:54Z","timestamp":1750164354000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3617376"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,16]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1,31]]}},"alternative-id":["10.1145\/3617376"],"URL":"https:\/\/doi.org\/10.1145\/3617376","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"value":"1556-4681","type":"print"},{"value":"1556-472X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,16]]},"assertion":[{"value":"2022-03-26","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-17","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-16","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}