Our Genomics experiments in this year mainly focus on improving the passage retrieval performance in the biomedical domain. We address this problem by constructing difierent indexes. In particular, we propose a method to build word-based index and sentence-based index for our experiments. The passage mean average precision (passage MAP) for our flrst run \york07ga1" using the word-based index was 0.095 and the passage MAP for our second run \york07ga2" using the sentence-based index was 0.086. However, the passage MAP for our third run \york07ga3" using both the word-based index and UMLS for query expansion degraded to 0.060. All these three o‐cial runs are automatic. The evaluation results show that using the word-based index is more efiective than using the sentence-based index for improving the passage retrieval performance. We flnd that pseudo-relevance feedback can make a positive contribution to the retrieval performance. However, we also flnd that query expansion using UMLS and Entrez Gene does not improve the retrieval performance, and in some cases it makes a negative contribution to the retrieval performance.
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