A classification approach to extract biological events

The machine learning methods like support vectors machines, hidden Markov model and conditional random fields are the most used methods for implementing natural language processing systems. In this paper, we propose a machine learning approach that can be used for sequential labeling tasks like biological event extraction. Our biological event extraction approach uses Support Vector Machines (SVM) and a composite kernel function to identify triggers and to assign the corresponding arguments. Also, we use a number of features based on both syntactic and contextual information which were automatically learned from the training data.