Conference Proceedings
SeeDev Binary Event Extraction using SVMs and a Rich Feature Set
NC Panyam, G Khirbat, K Verspoor, T Cohn, K Ramamohanarao
BioNLP-ST | The Association for Computational Linguistics | Published : 2016
DOI: 10.18653/v1/w16-3010
Abstract
This paper describes the system details and results of the participation of the team from the University of Melbourne in the SeeDev binary event extraction of BioNLP-Shared Task 2016. This task addresses the extraction of genetic and molecular mechanisms that regulate plant seed development from the natural language text of the published literature. In our submission, we developed a system1 using a support vector machine classifier with linear kernel powered by a rich set of features. Our system achieved an F1-score of 36.4%.