{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:10:59Z","timestamp":1775913059393,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T00:00:00Z","timestamp":1730073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key Research and Development Program of China under Grant","award":["2022ZD0118300"],"award-info":[{"award-number":["2022ZD0118300"]}]},{"name":"National Natural Science Foundation of China under Grant","award":["62302131"],"award-info":[{"award-number":["62302131"]}]},{"name":"National Natural Science Foundation of China under Grant","award":["62302130"],"award-info":[{"award-number":["62302130"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,28]]},"DOI":"10.1145\/3664647.3681702","type":"proceedings-article","created":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T06:59:27Z","timestamp":1729925967000},"page":"1274-1282","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Generalize to Fully Unseen Graphs: Learn Transferable Hyper-Relation Structures for Inductive Link Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4682-4839","authenticated-orcid":false,"given":"Jing","family":"Yang","sequence":"first","affiliation":[{"name":"Hainan University, Hainan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9773-1265","authenticated-orcid":false,"given":"Xiaowen","family":"Jiang","sequence":"additional","affiliation":[{"name":"Hainan University, Hainan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4096-9134","authenticated-orcid":false,"given":"Yuan","family":"Gao","sequence":"additional","affiliation":[{"name":"Hainan University, Hainan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7986-4244","authenticated-orcid":false,"given":"Laurence T.","family":"Yang","sequence":"additional","affiliation":[{"name":"Zhengzhou University &amp; St. Francis Xavier University, Zhengzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9584-2160","authenticated-orcid":false,"given":"Jieming","family":"Yang","sequence":"additional","affiliation":[{"name":"Hainan University, Hainan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,10,28]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"ISWC 2021, Virtual Event, October 24--28, 2021, Proceedings 20","author":"Ali Mehdi","year":"2021","unstructured":"Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, and Jens Lehmann. 2021. Improving inductive link prediction using hyper-relational facts. In The Semantic Web--ISWC 2021: 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24--28, 2021, Proceedings 20. 74--92."},{"key":"e_1_3_2_1_2_1","volume-title":"27th Annual Conference on Neural Information Processing Systems. 2787--2795","author":"Garc\u00edaDur\u00e1n Alberto Weston Usunier Nicolas","year":"2013","unstructured":"Usunier Nicolas Garc\u00edaDur\u00e1n Alberto Weston Jason Bordes, Antoine and Oksana Yakhnenko. 2013. Translating embeddings for modeling multirelational data. In 27th Annual Conference on Neural Information Processing Systems. 2787--2795."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/273"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531757"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3030076"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450141"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of the 10th International Conference on Learning Representations. 1--25","author":"Galkin Mikhail","year":"2022","unstructured":"Mikhail Galkin, Etienne Denis, Jiapeng Wu, and William L Hamilton. 2022. Nodepiece: Compositional and parameter-efficient representations of large knowledge graphs. In Proceedings of the 10th International Conference on Learning Representations. 1--25."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00098"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579051.3579066"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics. 249--256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics. 249--256."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/250"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 40th International Conference on Machine Learning. 18796--18809","author":"Jaejun Lee Chanyoung Chung","year":"2023","unstructured":"Chanyoung Chung Jaejun Lee and Joyce Jiyoung Whang. 2023. InGram: Inductive knowledge graph embedding via relation graphs. In Proceedings of the 40th International Conference on Machine Learning. 18796--18809."},{"key":"e_1_3_2_1_15_1","volume-title":"A survey on knowledge graphs: Representation, acquisition, and applications","author":"Ji Shaoxiong","year":"2021","unstructured":"Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and S Yu Philip. 2021. A survey on knowledge graphs: Representation, acquisition, and applications. IEEE transactions on neural networks and learning systems, Vol. 33, 2 (2021), 494--514."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-emnlp.168"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.900"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3282989"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of the 35th Conference on Neural Information Processing Systems. 2034--2045","author":"Liu Shuwen","year":"2021","unstructured":"Shuwen Liu, Bernardo Grau, Ian Horrocks, and Egor Kostylev. 2021. INDIGO: GNN-based inductive knowledge graph completion using pair-wise encoding.. In Proceedings of the 35th Conference on Neural Information Processing Systems. 2034--2045."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16554"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the 33rd Conference on Neural Information Processing Systems. 15347--15357","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 Conference on Neural Information Processing Systems. 15347--15357."},{"key":"e_1_3_2_1_23_1","volume-title":"Markus Hagenbuchner, and Gabriele Monfardini.","author":"Scarselli Franco","year":"2008","unstructured":"Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2008. The graph neural network model. IEEE transactions on neural networks, Vol. 20, 1 (2008), 61--80."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_1_25_1","volume-title":"International Conference on Machine Learning. 9448--9457","author":"Teru Komal","year":"2020","unstructured":"Komal Teru, Etienne Denis, and Will Hamilton. 2020. Inductive relation prediction by subgraph reasoning. In International Conference on Machine Learning. 9448--9457."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W15-4007"},{"key":"e_1_3_2_1_27_1","first-page":"1","article-title":"Knowledge graph completion via complex tensor factorization","volume":"18","author":"Trouillon Th\u00e9o","year":"2017","unstructured":"Th\u00e9o Trouillon, Christopher R Dance, \u00c9ric Gaussier, Johannes Welbl, Sebastian Riedel, and Guillaume Bouchard. 2017. Knowledge graph completion via complex tensor factorization. Journal of Machine Learning Research, Vol. 18, 130 (2017), 1--38.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the 8th International Conference on Learning Representations. 1--15","author":"Vashishth Shikhar","year":"2020","unstructured":"Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, and Partha Talukdar. 2020. Composition-based multi-relational graph convolutional networks. In Proceedings of the 8th International Conference on Learning Representations. 1--15."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20337"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.295"},{"key":"e_1_3_2_1_31_1","volume-title":"Knowledge graph embedding: A survey of approaches and applications","author":"Wang Quan","year":"2017","unstructured":"Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 2017. Knowledge graph embedding: A survey of approaches and applications. IEEE transactions on knowledge and data engineering, Vol. 29, 12 (2017), 2724--2743."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1060"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/325"},{"key":"e_1_3_2_1_34_1","volume-title":"Proceedings of the 3rd International Conference on Learning Representations. 1--12","author":"Yang Bishan","year":"2015","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 Proceedings of the 3rd International Conference on Learning Representations. 1--12."},{"key":"e_1_3_2_1_35_1","volume-title":"Proceedings of the 31st Conference on Neural Information Processing Systems. 2319--2328","author":"Yang Fan","year":"2017","unstructured":"Fan Yang, Zhilin Yang, and William W Cohen. 2017. Differentiable learning of logical rules for knowledge base reasoning. In Proceedings of the 31st Conference on Neural Information Processing Systems. 2319--2328."},{"key":"e_1_3_2_1_36_1","volume-title":"International conference on machine learning. 40--48","author":"Yang Zhilin","year":"2016","unstructured":"Zhilin Yang, William Cohen, and Ruslan Salakhudinov. 2016. Revisiting semi-supervised learning with graph embeddings. In International conference on machine learning. 40--48."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512008"},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of the 35th Conference on Neural Information Processing System. 29476--29490","author":"Zhu Zhaocheng","year":"2021","unstructured":"Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang. 2021. Neural bellman-ford networks: A general graph neural network framework for link prediction. In Proceedings of the 35th Conference on Neural Information Processing System. 29476--29490."}],"event":{"name":"MM '24: The 32nd ACM International Conference on Multimedia","location":"Melbourne VIC Australia","acronym":"MM '24","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 32nd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664647.3681702","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3664647.3681702","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:28Z","timestamp":1750295848000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664647.3681702"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,28]]},"references-count":38,"alternative-id":["10.1145\/3664647.3681702","10.1145\/3664647"],"URL":"https:\/\/doi.org\/10.1145\/3664647.3681702","relation":{},"subject":[],"published":{"date-parts":[[2024,10,28]]},"assertion":[{"value":"2024-10-28","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}