GrapAL: Connecting the Dots in Scientific Literature

Christine Betts, Joanna Power, Waleed Ammar


Abstract
We introduce GrapAL (Graph database of Academic Literature), a versatile tool for exploring and investigating a knowledge base of scientific literature that was semi-automatically constructed using NLP methods. GrapAL fills many informational needs expressed by researchers. At the core of GrapAL is a Neo4j graph database with an intuitive schema and a simple query language. In this paper, we describe the basic elements of GrapAL, how to use it, and several use cases such as finding experts on a given topic for peer reviewing, discovering indirect connections between biomedical entities, and computing citation-based metrics. We open source the demo code to help other researchers develop applications that build on GrapAL.
Anthology ID:
P19-3025
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Month:
July
Year:
2019
Address:
Florence, Italy
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
147–152
Language:
URL:
https://aclanthology.org/P19-3025
DOI:
10.18653/v1/P19-3025
Bibkey:
Cite (ACL):
Christine Betts, Joanna Power, and Waleed Ammar. 2019. GrapAL: Connecting the Dots in Scientific Literature. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 147–152, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
GrapAL: Connecting the Dots in Scientific Literature (Betts et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-3025.pdf
Data
Semantic Scholar