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‘HypothesisFinder:’ A Strategy for the Detection of Speculative Statements in Scientific Text.

Authors :
Malhotra, Ashutosh
Younesi, Erfan
Gurulingappa, Harsha
Hofmann-Apitius, Martin
Source :
PLoS Computational Biology; Jul2013, Vol. 9 Issue 7, p1-10, 10p
Publication Year :
2013

Abstract

Speculative statements communicating experimental findings are frequently found in scientific articles, and their purpose is to provide an impetus for further investigations into the given topic. Automated recognition of speculative statements in scientific text has gained interest in recent years as systematic analysis of such statements could transform speculative thoughts into testable hypotheses. We describe here a pattern matching approach for the detection of speculative statements in scientific text that uses a dictionary of speculative patterns to classify sentences as hypothetical. To demonstrate the practical utility of our approach, we applied it to the domain of Alzheimer's disease and showed that our automated approach captures a wide spectrum of scientific speculations on Alzheimer's disease. Subsequent exploration of derived hypothetical knowledge leads to generation of a coherent overview on emerging knowledge niches, and can thus provide added value to ongoing research activities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1553734X
Volume :
9
Issue :
7
Database :
Complementary Index
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
89626401
Full Text :
https://doi.org/10.1371/journal.pcbi.1003117