{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:06:05Z","timestamp":1772553965586,"version":"3.50.1"},"reference-count":76,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272219"],"award-info":[{"award-number":["62272219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872172"],"award-info":[{"award-number":["61872172"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/tnnls.2023.3262937","type":"journal-article","created":{"date-parts":[[2023,4,5]],"date-time":"2023-04-05T17:49:34Z","timestamp":1680716974000},"page":"11580-11594","source":"Crossref","is-referenced-by-count":18,"title":["Position-Aware Relational Transformer for Knowledge Graph Embedding"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2233-8470","authenticated-orcid":false,"given":"Guangyao","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4177-9199","authenticated-orcid":false,"given":"Zequn","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3635-6335","authenticated-orcid":false,"given":"Wei","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology and the National Institute of Healthcare Data Science, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3539-7776","authenticated-orcid":false,"given":"Gong","family":"Cheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}]},{"given":"Yuzhong","family":"Qu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1522"},{"key":"ref2","first-page":"864","article-title":"Low-rank bottleneck in multi-head attention models","volume-title":"Proc. ICML","author":"Bhojanapalli"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"ref4","first-page":"2787","article-title":"Translating embeddings for modeling multi-relational data","volume-title":"Proc. NIPS","author":"Bordes"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1140"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16850"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.617"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/556"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/209"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-77385-4_24"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"ref12","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. NAACL-HLT","author":"Devlin"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MWSCAS.2017.8053243"},{"key":"ref14","first-page":"1","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. ICLR","author":"Dosovitskiy"},{"key":"ref15","first-page":"1","article-title":"Deep graph matching consensus","volume-title":"Proc. ICLR","author":"Fey"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018739"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3019893"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"ref19","first-page":"2505","article-title":"Learning to exploit long-term relational dependencies in knowledge graphs","volume-title":"Proc. ICML","author":"Guo"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref21","first-page":"473","article-title":"LSTM can solve hard long time lag problems","volume-title":"Proc. NIPS","author":"Hochreiter"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.457"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3070843"},{"key":"ref24","first-page":"1","article-title":"Rethinking positional encoding in language pre-training","volume-title":"Proc. ICLR","author":"Ke"},{"key":"ref25","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. ICLR","author":"Kingma"},{"key":"ref26","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. ICLR","author":"Kipf"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487592"},{"key":"ref28","first-page":"3744","article-title":"Set transformer: A framework for attention-based permutation-invariant neural networks","volume-title":"Proc. ICML","author":"Lee"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3233\/SW-140134"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1274"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3083259"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3055147"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2022.10.001"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1082"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"ref36","first-page":"2168","article-title":"Analogical inference for multi-relational embeddings","volume-title":"Proc. ICML","author":"Liu"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.515"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1223"},{"key":"ref39","first-page":"1","article-title":"YAGO3: A knowledge base from multilingual Wikipedias","volume-title":"Proc. CIDR","author":"Mahdisoltani"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371804"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/219717.219748"},{"key":"ref42","first-page":"4696","article-title":"When does label smoothing help?","volume-title":"Proc. NeurIPS","author":"M\u00fcller"},{"key":"ref43","first-page":"809","article-title":"A three-way model for collective learning on multi-relational data","volume-title":"Proc. ICML","author":"Nickel"},{"issue":"1","key":"ref44","first-page":"140","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3424672"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.412"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2074"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.4324\/9780203786031-11"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68288-4_37"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/611"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5354"},{"key":"ref52","first-page":"3174","article-title":"BERT-INT: A BERT-based interaction model for knowledge graph alignment","volume-title":"Proc. IJCAI","author":"Tang"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1174"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301297"},{"key":"ref55","first-page":"2071","article-title":"Complex embeddings for simple link prediction","volume-title":"Proc. ICML","author":"Trouillon"},{"key":"ref56","first-page":"1","article-title":"Composition-based multi-relational graph convolutional networks","volume-title":"Proc. ICLR","author":"Vashishth"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref58","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. ICLR","author":"Velickovic"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450043"},{"key":"ref60","first-page":"1","article-title":"CoKE: Contextualized knowledge graph embedding","author":"Wang","year":"2020","journal-title":"CoRR"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2754499"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450118"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1032"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i16.17654"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/733"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1023"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.578"},{"key":"ref69","first-page":"1","article-title":"Embedding entities and relations for learning and inference in knowledge bases","volume-title":"Proc. ICLR","author":"Yang"},{"key":"ref70","first-page":"1","article-title":"KG-BERT: BERT for knowledge graph completion","author":"Yao","year":"2019","journal-title":"CoRR"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449925"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/194"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i03.5701"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3189994"},{"key":"ref75","first-page":"4258","article-title":"Iterative entity alignment via knowledge embeddings","volume-title":"Proc. IJCAI","author":"Zhu"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132912"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10623582\/10092525.pdf?arnumber=10092525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T18:12:41Z","timestamp":1722967961000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10092525\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":76,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2023.3262937","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}