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Parenthetically speaking: classifying the contents of parentheses for text mining.

Authors :
Cohen KB
Christiansen T
Hunter LE
Source :
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2011; Vol. 2011, pp. 267-72. Date of Electronic Publication: 2011 Oct 22.
Publication Year :
2011

Abstract

The contents of parentheses in biomedical text have many potential uses in text mining applications. However, making use of them requires the ability to determine what class of contents they are. A system that automatically classifies parenthesized text into one of 20 categories is presented and evaluated here. It performs at a micro-averaged accuracy of 68% and a macro-averaged accuracy of 60% on an annotated corpus. The application is available as a Java class and as a Perl module.

Details

Language :
English
ISSN :
1942-597X
Volume :
2011
Database :
MEDLINE
Journal :
AMIA ... Annual Symposium proceedings. AMIA Symposium
Publication Type :
Academic Journal
Accession number :
22195078