Lucene, MetaMap, and language modeling: OHSU at CLEF eHealth 2013

The Oregon Health & Science University team's participation in task #3 ("addressing patients' medical questions") of this year's eHealth CLEF campaign included submissions from two different retrieval systems. The first was a traditional, Lucene-based system modi fied from one used in previous years' TREC-med campaigns; the second was a novel system that used statistical language modeling techniques to perform text retrieval. Since 2013 was the first year of our participation in this campaign, our focus was on familiarizing ourselves with working on a corpus of web text, as well as putting together a proof-of-concept implementation of a language-model retrieval system. We submitted three runs in total; one from the novel system, and two from our Lucene-based system, one of which made use of the National Library of Medicine's MetaMap tool to perform query expansion. In general, our runs did not perform particularly well, although there were several topics for which our language model-based retrieval system produced the best P@10. Future work will focus on pre-indexing text normalization as well as a more sophisticated approach to query parsing.