Welbl, J;
Bouchard, G;
Riedel, S;
(2016)
A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion.
In:
Proceedings of the 5th Workshop on Automated Knowledge Base Construction.
(pp. pp. 103-107).
Association for Computational Linguistics (ACL): San Diego, CA, USA.
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Abstract
Embedding-based Knowledge Base Completion models have so far mostly combined distributed representations of individual entities or relations to compute truth scores of missing links. Facts can however also be represented using pairwise embeddings, i.e. embeddings for pairs of entities and relations. In this paper we explore such bigram embeddings with a flexible Factorization Machine model and several ablations from it. We investigate the relevance of various bigram types on the fb15k237 dataset and find relative improvements compared to a compositional model.
| Type: | Proceedings paper |
|---|---|
| Title: | A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion |
| Event: | 5th Workshop on Automated Knowledge Base Construction |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.18653/v1/W16-1319 |
| Publisher version: | https://doi.org/10.18653/v1/W16-1319 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10104709 |
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