SingleCite: Towards an improved Single Citation Search in PubMed
Lana Yeganova, Donald C Comeau, Won Kim, W John Wilbur, Zhiyong Lu
Abstract
A search that is targeted at finding a specific document in databases is called a Single Citation search. Single citation searches are particularly important for scholarly databases, such as PubMed, because users are frequently searching for a specific publication. In this work we describe SingleCite, a single citation matching system designed to facilitate user’s search for a specific document. We report on the progress that has been achieved towards building that functionality.- Anthology ID:
- W18-2318
- Volume:
- Proceedings of the BioNLP 2018 workshop
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Venue:
- BioNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 151–155
- Language:
- URL:
- https://aclanthology.org/W18-2318
- DOI:
- 10.18653/v1/W18-2318
- Cite (ACL):
- Lana Yeganova, Donald C Comeau, Won Kim, W John Wilbur, and Zhiyong Lu. 2018. SingleCite: Towards an improved Single Citation Search in PubMed. In Proceedings of the BioNLP 2018 workshop, pages 151–155, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- SingleCite: Towards an improved Single Citation Search in PubMed (Yeganova et al., BioNLP 2018)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W18-2318.pdf