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This article is part of the supplement: Proceedings of the BioNLP 08 ACL Workshop: Themes in biomedical language processing

Open Access Open Badges Research

Automatic inference of indexing rules for MEDLINE

Aurélie Névéol1*, Sonya E Shooshan1 and Vincent Claveau2

Author Affiliations

1 National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA

2 IRISA – CNRS, Campus de Beaulieu, 35042 Rennes, France

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BMC Bioinformatics 2008, 9(Suppl 11):S11  doi:10.1186/1471-2105-9-S11-S11

Published: 19 November 2008



Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE.


In this paper, we describe the use and the customization of Inductive Logic Programming (ILP) to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers.


Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI), a system producing automatic indexing recommendations for MEDLINE.


We expect the sets of ILP rules obtained in this experiment to be integrated into MTI.