A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization

Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung

[How to correct problems with metadata yourself]


Abstract
In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object). Our CapsE represents each triple as a 3-column matrix where each column vector represents the embedding of an element in the triple. This 3-column matrix is then fed to a convolution layer where multiple filters are operated to generate different feature maps. These feature maps are reconstructed into corresponding capsules which are then routed to another capsule to produce a continuous vector. The length of this vector is used to measure the plausibility score of the triple. Our proposed CapsE obtains better performance than previous state-of-the-art embedding models for knowledge graph completion on two benchmark datasets WN18RR and FB15k-237, and outperforms strong search personalization baselines on SEARCH17.
Anthology ID:
N19-1226
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Jill Burstein, Christy Doran, Thamar Solorio
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2180–2189
Language:
URL:
https://aclanthology.org/N19-1226
DOI:
10.18653/v1/N19-1226
Bibkey:
Cite (ACL):
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Phung. 2019. A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 2180–2189, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (Nguyen et al., NAACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/N19-1226.pdf
Code
 daiquocnguyen/CapsE +  additional community code
Data
FB15k-237WN18WN18RR