Automating document classification for the Immune Epitope Database.

ABSTRACT:

Background

The Immune Epitope Database contains information on immune epitopes curated manually from the scientific literature. Like similar projects in other knowledge domains, significant effort is spent on identifying which articles are relevant for this purpose.

Results

We here report our experience in automating this process using Naïve Bayes classifiers trained on 20,910 abstracts classified by domain experts. Improvements on the basic classifier performance were made by a) utilizing information stored in PubMed beyond the abstract itself b) applying standard feature selection criteria and c) extracting domain specific feature patterns that e.g. identify peptides sequences. We have implemented the classifier into the curation process determining if abstracts are clearl

SUBMITTER: Wang P 

PROVIDER: S-EPMC1965490 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature