Improving Spatial Semantic Analysis by a Combining Model

This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.