DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings

Viktor Schlegel, André Freitas


Abstract
This paper describes DBee, a database to support the construction of data-intensive AI applications. DBee provides a unique data model which operates jointly over large-scale knowledge graphs (KGs) and embedding vector spaces (VSs). This model supports queries which exploit the semantic properties of both types of representations (KGs and VSs). Additionally, DBee aims to facilitate the construction of KGs and VSs, by providing a library of generators, which can be used to create, integrate and transform data into KGs and VSs.
Anthology ID:
D19-5322
Volume:
Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
Month:
November
Year:
2019
Address:
Hong Kong
Venues:
EMNLP | TextGraphs | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
177–185
Language:
URL:
https://aclanthology.org/D19-5322
DOI:
10.18653/v1/D19-5322
Bibkey:
Cite (ACL):
Viktor Schlegel and André Freitas. 2019. DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings. In Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13), pages 177–185, Hong Kong. Association for Computational Linguistics.
Cite (Informal):
DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings (Schlegel & Freitas, EMNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-5322.pdf