Using argumentation to extract key sentences from biomedical abstracts

s from Biomedical Abstracts Patrick Rucha , Celia Boyer c , Christine Chichesterb , Imad Tbahritiab Antoine Geissbühlera , Paul Fabrya , Julien Gobeilla , Violaine Pilletab , Dietrich Rebholz-Schuhmannd , Christian Lovisa , Anne-Lise Veutheyb a SIM, University Hospitals of Geneva, Geneva, CH b Swiss-Prot Group, Swiss Institute of Bioinformatics, Geneva, CH; c Health-on-the-Net Foundation, Geneva, CH; d European Bioinformatics Institute ,Hinxton, UK PROBLEM: Key word assignment has been largely used in MEDLINE to provide an indicative “gist” of the content of articles and to help retrieving biomedical . Abstracts are also used for this purpose. However with usually more than s, MEDLINE abstracts can still be regarded as long documents; therefore we design a system to select a unique key sentence. This key sentence must be ve of the article’s content and we assume that abstract’s conclusions are good candidates. We design and assess the performance of an automatic key sentence ...

• Type: Journal
• Year: 2007
• Where: IJMI
• Authors: Patrick Ruch, Célia Boyer, Christine Chichester, Imad Tbahriti, Antoine Geissbühler, Paul Fabry, Julien Gobeill, Violaine Pillet, Dietrich Rebholz-Schuhmann, Christian Lovis, Anne-Lise Veuthey
• Keywords: Abstracts Patrick Rucha, Geneva, IJMI 2007, Key Sentence