在本論文中，我們提出一個新方法，利用網路資源對雙語平行的句子做辭彙對應。我們的方法首先將平行句中的詞彙轉換成擴充查詢式，送至搜尋引擎查回多筆摘要，接著從摘要中統計出最有可能互為翻譯的單字和詞組。同時我們會計算出一些必要的特徵值，以便於能夠更精確的找出正確的辭彙對應。最後，我們從查詢回來的摘要中以特徵值對候選者進行過濾、計分與排序，挑選出最可能互為翻譯的單字和詞組。實驗結果顯示，我們的方法對於詞彙對應與克服資料稀疏的問題有顯著的效果。

We introduce a method for aligning words and phrases in a given pair of bilingual sentence using the Web as corpus. In our approach, each Chinese word and all English words are transformed into an query, sent to the search engine to retrieve mixed-code snippets. We use the returned snippets to align words and phrases such that the word and aligned word or phrase are likely to be translation counterparts. The method involves calculating features of alignment candidates, filtering candidates, scoring candidates, and ranking candidates. Finally, we select the most likely word or phrase alignment for each source word. The results show that the method can reach 53.2% recall and 88.6% precision.

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