TransRHS: a representation learning method for knowledge graphs with relation hierarchical structure Zhang, Fuxiang, Wang, Xin, Li, Zhao and Li, Jianxin 2020, TransRHS: a representation learning method for knowledge graphs with relation hierarchical structure, in IJCAI 2020 : Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI, [Yokohama, Japan], pp. 2987-2993, doi: 10.24963/ijcai.2020/413. Attached Files Name Description MIMEType Size Downloads Title TransRHS: a representation learning method for knowledge graphs with relation hierarchical structure Author(s) Zhang, Fuxiang Wang, Xin Li, Zhao Li, Jianxin orcid.org/0000-0002-9059-330X Conference name Artificial Intelligence. Conference (29th : 2020 : Yokohama, Japan) Conference location Yokohama, Japan Conference dates 2020/07/11 - 2020/07/17 Title of proceedings IJCAI 2020 : Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Editor(s) Bessiere, C Publication date 2020 Series Artificial Intelligence Conference Start page 2987 End page 2993 Total pages 7 Publisher IJCAI Place of publication [Yokohama, Japan] Keyword(s) Machine Learning Knowledge-based Learning Natural Language Processing Embeddings ISBN 978-0-9992411-6-5 Language eng DOI 10.24963/ijcai.2020/413 Indigenous content off HERDC Research category E1 Full written paper - refereed Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30140922 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 18 Aug 2020, 11:22:46 EST Wed, 19 Aug 2020, 05:00:26 EST Wed, 19 Aug 2020, 06:04:45 EST Fri, 11 Sep 2020, 14:49:13 EST Fri, 11 Sep 2020, 14:51:26 EST Tue, 29 Sep 2020, 10:37:02 EST Sat, 26 Dec 2020, 01:30:32 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 51 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Tue, 18 Aug 2020, 11:22:46 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.