Abstract
The scientific literature is one of the main sources of information for researchers. However, due to the rapid increase of the number of scientific articles, satisfying a specific information need has become a very demanding task, and researchers often have to scan through a large number of publications in search of a specific nugget of information. In this work we propose the use of supervised machine learning techniques to retrieve and rank sentences describing different types of biomolecular events. The objective is to classify and rank sentences that match any general query according to the likelihood of mentioning events involving one or more biomolecular entities. These ranked results should provide a condensed, or summarized, view of the knowledge present in the literature and related to the user’s information need.
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Nunes, T., Matos, S., Oliveira, J.L. (2014). Extracting Sentences Describing Biomolecular Events from the Biomedical Literature. In: Omatu, S., Bersini, H., Corchado, J., Rodríguez, S., Pawlewski, P., Bucciarelli, E. (eds) Distributed Computing and Artificial Intelligence, 11th International Conference. Advances in Intelligent Systems and Computing, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-319-07593-8_48
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DOI: https://doi.org/10.1007/978-3-319-07593-8_48
Publisher Name: Springer, Cham
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