A Feature Combination Method for Semantic Role Classification

摘要

This paper proposes a Chinese semantic role classification approach on the basis of feature combination. First we define a set of effective basic features. Then a statistics-based feature combination method is developed for constructing a combined feature set from the basic feature set. According to the distribution of each combined feature in positive and negative instances, we utilize a new statistics to measure the classifying performance of the feature, and then put the features with high ratio in the combined feature set. Finally, the semantic roles are classified by SVM classifier using both basic and combined feature set. The experimental results on Chinese Proposition Bank show that the method can improve the performance of SRC by two percent.