Bioinformatics
Semantic retrieval for the accurate identification of relational concepts in massive textbases
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Bioinformatics
Overview of BioNLP'09 shared task on event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
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Rapid advances in science and in laboratorial and computing methods are generating vast amounts of data and scientific literature. In order to keep up-to-date with the expanding knowledge in their field of study, researchers are facing an increasing need for tools that help manage this information. In the genomics field, various databases have been created to save information in a formalized and easily accessible form. However, human curators are not capable of updating these databases at the same rate new studies are published. Advanced and robust text mining tools that automatically extract newly published information from scientific articles are required. This paper presents a methodology, based on syntactic parsing, for identification of gene events from the scientific literature. Evaluation of the proposed approach, based on the BioNLP shared task on event extraction, produced an average F-score of 47.1, for six event types.