Natural language processing in aid of FlyBase curators.
BACKGROUND
Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear.


RESULTS
PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowser's navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article.


CONCLUSIONS
We show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully.
Karamanis
Nikiforos
N
Computer Laboratory, University of Cambridge, William Gates Building, Cambridge, CB3 0FD, UK. nikiforos.karamanis@cl.cam.ac.uk
Seal
Ruth
R
Lewin
Ian
I
McQuilton
Peter
P
Vlachos
Andreas
A
Gasperin
Caroline
C
Drysdale
Rachel
R
Briscoe
Ted
T
D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D016206:Databases, Bibliographic; D016247:Information Storage and Retrieval / Q000379:methods; D009323:Natural Language Processing; D010506:Periodicals as Topic; D012984:Software; D018875:Vocabulary, Controlled