{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:18:57Z","timestamp":1750220337120,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 61902270 and No. 61802273"],"award-info":[{"award-number":["No. 61902270 and No. 61802273"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Jiangsu Higher Education Institutions of China","award":["No. 19KJA610002 and No. 19KJB520050"],"award-info":[{"award-number":["No. 19KJA610002 and No. 19KJB520050"]}]},{"name":"Postdoctoral Science Foundation of China","award":["No. 2020M681529"],"award-info":[{"award-number":["No. 2020M681529"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,26]]},"DOI":"10.1145\/3459637.3482367","type":"proceedings-article","created":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T15:31:19Z","timestamp":1636990279000},"page":"2637-2646","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Meta-Learning Based Hyper-Relation Feature Modeling for Out-of-Knowledge-Base Embedding"],"prefix":"10.1145","author":[{"given":"Yufeng","family":"Zhang","sequence":"first","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiqing","family":"Wang","sequence":"additional","affiliation":[{"name":"Monash University, Melbourne, VIC, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajie","family":"Xu","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"An","family":"Liu","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1785162.1785216"},{"volume-title":"Dong Bok Lee, and Sung Ju Hwang","year":"2020","author":"Baek Jinheon","key":"e_1_3_2_2_2_1"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/2999792.2999923"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/2900423.2900470"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/2898607.2898816"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"Mingyang Chen Wen Zhang Wei Zhang Qiang Chen and Huajun Chen. 2019. Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs. In EMNLP-IJCNLP. 4216--4225.  Mingyang Chen Wen Zhang Wei Zhang Qiang Chen and Huajun Chen. 2019. Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs. In EMNLP-IJCNLP. 4216--4225.","DOI":"10.18653\/v1\/D19-1431"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"crossref","unstructured":"Tim Dettmers Pasquale Minervini Pontus Stenetorp and Sebastian Riedel. 2018. Convolutional 2D Knowledge Graph Embeddings. In AAAI. 1811--1818.  Tim Dettmers Pasquale Minervini Pontus Stenetorp and Sebastian Riedel. 2018. Convolutional 2D Knowledge Graph Embeddings. In AAAI. 1811--1818.","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"crossref","unstructured":"Boyang Ding Quan Wang Bin Wang and Li Guo. 2018. Improving Knowledge Graph Embedding Using Simple Constraints. In ACL. 110--121.  Boyang Ding Quan Wang Bin Wang and Li Guo. 2018. Improving Knowledge Graph Embedding Using Simple Constraints. In ACL. 110--121.","DOI":"10.18653\/v1\/P18-1011"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"Shu Guo Quan Wang Lihong Wang Bin Wang and Li Guo. 2018. Knowledge Graph Embedding With Iterative Guidance From Soft Rules. In AAAI. 4816--4823.  Shu Guo Quan Wang Lihong Wang Bin Wang and Li Guo. 2018. Knowledge Graph Embedding With Iterative Guidance From Soft Rules. In AAAI. 4816--4823.","DOI":"10.1609\/aaai.v32i1.11918"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/3172077.3172138"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.5555\/3294771.3294869"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"crossref","unstructured":"Yanchao Hao Yuanzhe Zhang Kang Liu Shizhu He Zhanyi Liu Hua Wu and Jun Zhao. 2017. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge. In ACL. 221--231.  Yanchao Hao Yuanzhe Zhang Kang Liu Shizhu He Zhanyi Liu Hua Wu and Jun Zhao. 2017. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge. In ACL. 221--231.","DOI":"10.18653\/v1\/P17-1021"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411865"},{"volume-title":"Kingma and Jimmy Ba","year":"2015","author":"Diederik","key":"e_1_3_2_2_15_1"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.5555\/2886521.2886624"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Deepak Nathani Jatin Chauhan Charu Sharma and Manohar Kaul. 2019. Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. In ACL. 4710--4723.  Deepak Nathani Jatin Chauhan Charu Sharma and Manohar Kaul. 2019. Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. In ACL. 4710--4723.","DOI":"10.18653\/v1\/P19-1466"},{"key":"e_1_3_2_2_18_1","unstructured":"Arvind Neelakantan Benjamin Roth and Andrew McCallum. 2015. Compositional Vector Space Models for Knowledge Base Completion. In ACL. 156--166.  Arvind Neelakantan Benjamin Roth and Andrew McCallum. 2015. Compositional Vector Space Models for Knowledge Base Completion. In ACL. 156--166."},{"volume-title":"Dat Quoc Nguyen, and Dinh Q. Phung.","year":"2018","author":"Nguyen Dai Quoc","key":"e_1_3_2_2_19_1"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2483592"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.5555\/3104482.3104584"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2187836.2187874"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Evgenia Wasserman Pritsker William W. Cohen and Einat Minkov. 2015. Learning to Identify the Best Contexts for Knowledge-based WSD. In EMNLP. 1662--1667.  Evgenia Wasserman Pritsker William W. Cohen and Einat Minkov. 2015. Learning to Identify the Best Contexts for Knowledge-based WSD. In EMNLP. 1662--1667.","DOI":"10.18653\/v1\/D15-1192"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"crossref","unstructured":"Michael Sejr Schlichtkrull Thomas N. Kipf Peter Bloem Rianne van den Berg Ivan Titov and Max Welling. 2018. Modeling Relational Data with Graph Convolutional Networks. In ESWC. 593--607.  Michael Sejr Schlichtkrull Thomas N. Kipf Peter Bloem Rianne van den Berg Ivan Titov and Max Welling. 2018. Modeling Relational Data with Graph Convolutional Networks. In ESWC. 593--607.","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Baoxu Shi and Tim Weninger. 2018. Open-World Knowledge Graph Completion. In AAAI. 1957--1964.  Baoxu Shi and Tim Weninger. 2018. Open-World Knowledge Graph Completion. In AAAI. 1957--1964.","DOI":"10.1609\/aaai.v32i1.11535"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.5555\/3294996.3295163"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"crossref","unstructured":"Kristina Toutanova and Danqi Chen. 2015. Observed versus latent features for knowledge base and text inference. In CVSC. 57--66.  Kristina Toutanova and Danqi Chen. 2015. Observed versus latent features for knowledge base and text inference. In CVSC. 57--66.","DOI":"10.18653\/v1\/W15-4007"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045609"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"Peifeng Wang Jialong Han Chenliang Li and Rong Pan. 2019. Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding. In AAAI. 7152--7159.  Peifeng Wang Jialong Han Chenliang Li and Rong Pan. 2019. Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding. In AAAI. 7152--7159.","DOI":"10.1609\/aaai.v33i01.33017152"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.5555\/2893873.2894046"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.5555\/3298483.3298685"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/3172077.3172327"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.5555\/3060832.3061036"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806456"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Wenhan Xiong Thien Hoang and William Yang Wang. 2017. DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning. In EMNLP. 564--573.  Wenhan Xiong Thien Hoang and William Yang Wang. 2017. DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning. In EMNLP. 564--573.","DOI":"10.18653\/v1\/D17-1060"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Wenhan Xiong Mo Yu Shiyu Chang Xiaoxiao Guo and William Yang Wang. 2018. One-Shot Relational Learning for Knowledge Graphs. In EMNLP. 1980--1990.  Wenhan Xiong Mo Yu Shiyu Chang Xiaoxiao Guo and William Yang Wang. 2018. One-Shot Relational Learning for Knowledge Graphs. In EMNLP. 1980--1990.","DOI":"10.18653\/v1\/D18-1223"},{"volume-title":"Mitchell","year":"2017","author":"Yang Bishan","key":"e_1_3_2_2_37_1"},{"key":"e_1_3_2_2_38_1","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 ICLR. 1--12.  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 ICLR. 1--12."},{"volume-title":"Chawla","year":"2020","author":"Zhang Chuxu","key":"e_1_3_2_2_39_1"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313612"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Zhao Zhang Fuzhen Zhuang Meng Qu Fen Lin and Qing He. 2018. Knowledge Graph Embedding with Hierarchical Relation Structure. In EMNLP. 3198--3207.  Zhao Zhang Fuzhen Zhuang Meng Qu Fen Lin and Qing He. 2018. Knowledge Graph Embedding with Hierarchical Relation Structure. In EMNLP. 3198--3207.","DOI":"10.18653\/v1\/D18-1358"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"crossref","unstructured":"Yukun Zuo Quan Fang Shengsheng Qian Xiaorui Zhang and Changsheng Xu. 2018. Representation Learning of Knowledge Graphs with Entity Attributes and Multimedia Descriptions. In BigMM. 1--5.  Yukun Zuo Quan Fang Shengsheng Qian Xiaorui Zhang and Changsheng Xu. 2018. Representation Learning of Knowledge Graphs with Entity Attributes and Multimedia Descriptions. In BigMM. 1--5.","DOI":"10.1109\/BigMM.2018.8499179"}],"event":{"name":"CIKM '21: The 30th ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Virtual Event Queensland Australia","acronym":"CIKM '21"},"container-title":["Proceedings of the 30th ACM International Conference on Information & Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482367","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459637.3482367","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:23Z","timestamp":1750191143000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3459637.3482367"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":42,"alternative-id":["10.1145\/3459637.3482367","10.1145\/3459637"],"URL":"https:\/\/doi.org\/10.1145\/3459637.3482367","relation":{},"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"2021-10-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}