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Natural Language Processing in aid of FlyBase curators

Nikiforos Karamanis12, Ruth Seal2, Ian Lewin1*, Peter McQuilton2, Andreas Vlachos1, Caroline Gasperin1, Rachel Drysdale2 and Ted Briscoe1

Author Affiliations

1 Computer Laboratory, University of Cambridge, William Gates Building, Cambridge, CB3 0FD, UK

2 Department of Genetics, University of Cambridge, Downing Site, Cambridge, CB2 3EH, UK

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BMC Bioinformatics 2008, 9:193  doi:10.1186/1471-2105-9-193

Published: 14 April 2008

Abstract

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.

Conclusion

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.