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
- Editors:
- Marta R. Costa-jussà, Enrique Alfonseca
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/P19-3025.pdf
- Data
- Semantic Scholar