Chinese Sentence Similarity Measure Based on Words and Structure Information

Example-based machine translation (EBMT) is an important branch of machine translation. Sentence similarity measure is certainly one of the most significant problems addressed in EBMT. For EBMT from Chinese to English, the performance of similarity measure of Chinese sentences greatly affects the final translation result of an input Chinese sentence. In this paper, we present an approach to Chinese sentence similarity measure (CSSM) together with word sequence and sentence structure information. The new method in our experiments yields a good efficiency and effectiveness without conducting a complex and deep syntactic analysis of Chinese sentences, which can be applied to an EBMT system for CSSM for a better performance in Chinese-to-English translation.