Paper: Using Argumentation To Retrieve Articles With Similar Citations From MEDLINE

ACL ID W04-1202
Title Using Argumentation To Retrieve Articles With Similar Citations From MEDLINE
Venue International Joint Workshop On Natural Language Processing In Biomedicine And Its Applications NLPBA BioNLP
Session
Year 2004
Authors
  • Imad Tbahriti (Geneva Bioinformatics, Geneva Switzerland; University of Geneva, Geneva Switzerland)
  • Christine Chichester (Geneva Bioinformatics, Geneva Switzerland)
  • Frederique Lisacek (Geneva Bioinformatics, Geneva Switzerland; Swiss Institute of Bioinformatics, Geneva Switzerland)
  • Patrick Ruch (Ecole Polytechnique Federale de Lausanne, Lausanne Switzerland)

The aim of this study is to investigate the relationships between citations and the scientific argumentation found in the abstract. We extracted citation lists from a set of 3200 full-text papers originating from a narrow domain. In parallel, we recovered the corresponding MEDLINE records for analysis of the argumentative moves. Our argumentative model is founded on four classes: PURPOSE, METHODS, RESULTS, and CONCLUSION. A Bayesian classifier trained on explicitly structured MEDLINE abstracts generates these argumentative categories. The categories are used to generate four different argumentative indexes. A fifth index contains the complete abstract, together with the title and the list of Medical Subject Headings (MeSH) terms. To appraise the relationship of the moves to the citations, ...