A4 Refereed article in a conference publication
Extracting protein-protein interaction sentences by applying rough set data analysis
Authors: Ginter F, Pahikkala T, Pyysalo S, Boberg J, Jarvinen J, Salakoski T
Editors: Tsumoto Husaku, Slowinski Roman, Komorowski Jan, Grzymala-Busse Jerzy W
Conference name: Fourth International Conference on Rough Sets and Current Trends in Computing
Publication year: 2004
Journal: Lecture Notes in Computer Science
Book title : Proceedings of the Fourth International Conference on Rough Sets and Current Trends in Computing
Journal name in source: ROUGH SETS AND CURRENT TRENDS IN COMPUTING
Journal acronym: LECT NOTES ARTIF INT
Volume: 3066
First page : 780
Last page: 785
Number of pages: 6
ISBN: 3-540-22117-4
ISSN: 0302-9743
In this paper, we introduce away to apply rough set data analysis to the problem of extracting protein-protein interaction sentences in biomedical literature. Our approach builds on decision rules of protein names, interaction words, and their mutual positions in sentences. In order to broaden the set of potential interaction words, we develop a morphological model which generates spelling and inflection variants of the interaction words. We evaluate the performance of the proposed method on a hand-tagged dataset of 1894 sentences and show a precision-recall break-even performance of 79,8% by using leave-one-out cross-validation.
