Experiments on the use of corpus-based word BI-gram in Chinese word segmentation

The first step of Chinese language processing is to segment a Chinese sentence into a sequence of words due to the fact that there is no original separation between adjacent words. An efficient corpus-based statistical method is adopted here to address such a problem. In this paper, some word BI-gram statistical measures derived from corpus are employed to remove the segmentation ambiguities. To segment a Chinese sentence, a bidirectional maximum matching method is firstly used to do pre-matching in order to get segmentation candidates and locate possible ambiguities. The statistical measures based on word Bi-gram information and word frequency will be used to construct a discriminate function, which is applied to ambiguity strings in order to get an utmost correct segmentation. Experimental results are analyzed to describe the features and limitations of this approach, and preliminary results indicate that our approach is compared favorably to other existing techniques.