We applied concept recognition techniques to the Genomics track primary and secondary tasks. For the primary task, we developed a foundational information retrieval system which incorporated Entrez Gene entries and UMLS concepts for query expansion via phrasal and term boosting representations of synonyms. For the secondary task, we evaluated three conceptual features-mouse strain names, indexed MeSH terms, and normalized citations-in addition to two surface linguistic features-BOW and bigrams. Our final feature set yielded consistently high F-measures.
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