In this paper, we present a system for information retrieval of biomedical texts at passage level. Our system used KL-divergence as the underlying retrieval model. We further added query expansion and performed post-processing on the results. We were able to obtain a Document MAP of 0.3563, Passage MAP of 0.0464 and Aspect MAP of 0.2255 on one of the three runs.
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