Finiding Gene Function using LitMiner

NRC (National Research Council, Canada) submitted 2 sets of results for the primary task in the TREC Genome track. The systems that generated these results were tuned primarily to achieve very high recall (above 90%) and secondarily to minimize the number of documents retrieved. Both submitted sets were the outputs of automatic systems (non-interactive, non-supervised) with a modular architecture. The TREC evaluation confirmed that recall for both submissions was extremely high: 543 out of 566 target documents (0.9594) were returned. In addition, these systems returned far fewer documents than were allowed by the genomic track rules. They returned an average of 196 documents per query across the 50 queries, with a median value of only 100 documents. For the first submission, the system was entirely based on Information Retrieval techniques, tuned to achieve very high recall and fair precision. Averaged precision was 0.3941 for the first submission. This first submission ranked third out of 49 runs submitted by all participants. For the second submission, reranking was done based on the outcome of an information extraction module, tuned towards the task of identifying gene function papers. This module identified 539 documents as highly promising; 121 of these turned out to be target documents, 418 weren't. All in all this caused the averaged precision to drop slightly to 0.3771 contrary to our expectations. This second submission ranked fifth out of all 49 runs.