{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T22:32:49Z","timestamp":1778106769040,"version":"3.51.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p>Entity alignment aims to link entities and their counterparts among multiple knowledge graphs (KGs). Most existing methods typically rely on external information of entities such as Wikipedia links and require costly manual feature construction to complete alignment. In this paper, we present a novel approach for entity alignment via joint knowledge embeddings. Our method jointly encodes both entities and relations of various KGs into a unified low-dimensional semantic space according to a small seed set of aligned entities. During this process, we can align entities according to their semantic distance in this joint semantic space. More specifically, we present an iterative and parameter sharing method to improve alignment performance. Experiment results on real-world datasets show that, as compared to baselines, our method achieves significant improvements on entity alignment, and can further improve knowledge graph completion performance on various KGs with the favor of joint knowledge embeddings.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/595","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T09:14:07Z","timestamp":1501233247000},"page":"4258-4264","source":"Crossref","is-referenced-by-count":259,"title":["Iterative Entity Alignment via Joint Knowledge Embeddings"],"prefix":"10.24963","author":[{"given":"Hao","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, State Key Lab on Intelligent Technology and Systems, National Lab for Information Science and Technology, Tsinghua University, Beijing, China"}]},{"given":"Ruobing","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Lab on Intelligent Technology and Systems, National Lab for Information Science and Technology, Tsinghua University, Beijing, China"}]},{"given":"Zhiyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"},{"name":"Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, China"}]},{"given":"Maosong","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China"},{"name":"Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou 221009 China"}]}],"member":"10584","event":{"name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"IJCAI-2017","number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"start":{"date-parts":[[2017,8,19]]},"end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T11:54:41Z","timestamp":1501242881000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/595"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/595","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}