A major obstacle to the construction of a probabilistic translation model is the lack of large parallel corpora. In this paper we first describe a parallel text mining system that finds parallel texts automatically on the Web. The generated Chinese-English parallel corpus is used to train a probabilistic translation model which translates queries for Chinese-English cross-language information retrieval (CLIR). We will discuss some problems in translation model training and show the preliminary CUR results.