A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Extracting protein-protein interaction sentences by applying rough set data analysis
Tekijät: Ginter F, Pahikkala T, Pyysalo S, Boberg J, Jarvinen J, Salakoski T
Toimittaja: Tsumoto Husaku, Slowinski Roman, Komorowski Jan, Grzymala-Busse Jerzy W
Konferenssin vakiintunut nimi: Fourth International Conference on Rough Sets and Current Trends in Computing
Julkaisuvuosi: 2004
Journal: Lecture Notes in Computer Science
Kokoomateoksen nimi: Proceedings of the Fourth International Conference on Rough Sets and Current Trends in Computing
Tietokannassa oleva lehden nimi: ROUGH SETS AND CURRENT TRENDS IN COMPUTING
Lehden akronyymi: LECT NOTES ARTIF INT
Vuosikerta: 3066
Aloitussivu: 780
Lopetussivu: 785
Sivujen määrä: 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.
