{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T16:13:38Z","timestamp":1783700018410,"version":"3.55.0"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","funder":[{"name":"Sichuan Science and Technology Program","award":["2019YFG0535"],"award-info":[{"award-number":["2019YFG0535"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61832001"],"award-info":[{"award-number":["61832001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tkde.2021.3110898","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T20:19:39Z","timestamp":1631132379000},"page":"1-1","source":"Crossref","is-referenced-by-count":39,"title":["DRGI: Deep Relational Graph Infomax for Knowledge Graph Completion"],"prefix":"10.1109","author":[{"given":"Shuang","family":"Liang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiasheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-76298-0_52"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2629489"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W15-4007"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"ref6","article-title":"Deep graph infomax","volume-title":"Proc. 7th Int. Conf. Learn. Representations","author":"Velickovic"},{"key":"ref7","first-page":"2787","article-title":"Translating embeddings for modeling multi-relational data","volume-title":"Proc. 26th Int. Conf. Neural Inf. Process. Syst.","author":"Bordes"},{"key":"ref8","article-title":"Rotate: Knowledge graph embedding by relational rotation in complex space","volume-title":"Proc. 7th Int. Conf. Learn. Representations","author":"Sun"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1522"},{"key":"ref10","first-page":"926","article-title":"Reasoning with neural tensor networks for knowledge base completion","volume-title":"Proc. 26th Int. Conf. Neural Inf. Process. Syst.","author":"Socher"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623623"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30493-5_52"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013060"},{"key":"ref15","article-title":"Embedding entities and relations for learning and inference in knowledge bases","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Yang"},{"key":"ref16","first-page":"2071","article-title":"Complex embeddings for simple link prediction","volume-title":"Proc. 33rd Int. Conf. Mach. Learn.","author":"Trouillon"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806502"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1219"},{"key":"ref19","article-title":"From one point to A manifold: Orbit models for knowledge graph embedding","author":"Xiao","year":"2015"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893920"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2638425"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2931548"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICBK50248.2020.00056"},{"key":"ref24","first-page":"809","article-title":"A three-way model for collective learning on multi-relational data","volume-title":"Proc. 28th Int. Conf. Mach. Learn.","author":"Nickel"},{"key":"ref25","first-page":"2168","article-title":"Analogical inference for multi-relational embeddings","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Liu"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v25i1.7917"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/n18-2053"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3005952"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2951103"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.23919\/JCC.2019.12.001"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1466"},{"key":"ref32","article-title":"Entity alignment for knowledge graphs with multi-order convolutional networks","author":"Nguyen","year":"2020","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref33","article-title":"Composition-based multi-relational graph convolutional networks","volume-title":"Proc. 8th Int. Conf. Learn. Representations","author":"Vashishth"},{"key":"ref34","first-page":"530","article-title":"Mutual information neural estimation","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Belghazi"},{"key":"ref35","article-title":"Learning deep representations by mutual information estimation and maximization","volume-title":"Proc. 7th Int. Conf. Learn. Representations","author":"Hjelm"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d18-1362"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273551"},{"key":"ref38","first-page":"2731","article-title":"Quaternion knowledge graph embeddings","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref39","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Kingma"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401172"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"ref42","first-page":"1535","article-title":"Identifying relations for open information extraction","volume-title":"Proc. Conf. Empirical Methods Natural Lang. Process.","author":"Fader"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/4358933\/09531531.pdf?arnumber=9531531","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:07:51Z","timestamp":1705014471000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9531531\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/tkde.2021.3110898","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}