中文摘要：

命名实体和新词、术语的翻译对机器翻译、跨语言检索、自动问答等系统的性能有着重要的影响，但是这些翻译很难从现有的翻译词典中获得。该文提出了一种从中文网页中自动获取高质量双语翻译对的方法。该方法利用网页中双语翻译对的特点，使用统计判别模型，融合多种识别特征自动挖掘网站中存在的双语翻译对。实验结果表明，采用该模型构建的双语翻译词表，TOP1的正确率达到82．1％，TOP3的正确率达到94．5％。文中还提出了一种利用搜索引擎验证候选翻译的方法，经过验证，TOP1的正确率可以提高到84．3％。

英文摘要：

The translations of named entities, out of vocabulary words and terms play an important role in many application systems such as machine translation, cross-language information retrieval and question answer. However, these translations are hard to access from traditional bilingual dictionary. This paper proposes a method to automatically extract high quality translation pairs from Chinese web corpora. It analyzes the features of bilingual translation pairs in web pages, and then a statistical discriminative model combined with multiple features is used to extract translation pairs. Experimental results show that the quality of the extracted bilingual translations is improved greatly： Top 1 accuracy 82.1%, and Top 3 94.5 %. The paper also proposes a verification method to further improve the accuracy of the initial extractions with the help of search engines. Top 1 accuracy grows up to 84.3% after the verification.