Automatic Indexing of Specialized Documents: Using Generic vs. Domain-Specific Document Representations

The shift from paper to electronic documents has caused the curation of information sources in large electronic databases to become more generalized. In the biomedical domain, continuing efforts aim at refining indexing tools to assist with the update and maintenance of databases such as MEDLINE. In this paper, we evaluate two statistical methods of producing MeSH indexing recommendations for the genetics literature, including recommendations involving subheadings, which is a novel application for the methods. We show that a generic representation of the documents yields both better precision and recall. We also find that a domainspecific representation of the documents can contribute to enhancing recall.