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
Venues:
ACL | BioNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
151–155
Language:
URL:
https://aclanthology.org/W18-2318
DOI:
10.18653/v1/W18-2318
Bibkey:
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., 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-2318.pdf