Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts-Reference-Cited by-同舟云学术

Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts

Published:2019-07-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
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Author:

Hao Junheng¹,Chen Muhao¹,Yu Wenchao¹,Sun Yizhou¹,Wang Wei¹

Affiliation:

1. University of California Los Angeles, Los Angeles, CA, USA

Funder

NSF DBI-1565137

DGE-1829071

U01HG008488

NIH R01GM115833

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3292500.3330838

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3. Antoine Bordes Jason Weston and Nicolas Usunier. 2014b. Open question answering with weakly supervised embedding models. In ECML-PKDD. Antoine Bordes Jason Weston and Nicolas Usunier. 2014b. Open question answering with weakly supervised embedding models. In ECML-PKDD.

4. Muhao Chen Yingtao Tian Xuelu Chen Zijun Xue and Carlo Zaniolo. 2018b. On2Vec: Embedding-based Relation Prediction for Ontology Population. In SDM. Muhao Chen Yingtao Tian Xuelu Chen Zijun Xue and Carlo Zaniolo. 2018b. On2Vec: Embedding-based Relation Prediction for Ontology Population. In SDM.

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