由於網際網路的普及化，人們可比以往更容易地取得資料，但這也導致了資訊過量的問題，除此之外，還存在著資訊重複的問題。以電子新聞為例，現在線上電子新聞網站林立，各個網站可能以不同的論點陳述著相同的事件，使用者若想窺知事情全貌，就需花費大量時間到各個電子新聞網站搜尋、瀏覽相關的事件，只有在搜集、閱讀完所有報導後，才有可能取得完整資訊。然而對忙碌的現代人來說，並沒有這麼多的時間來搜集、閱讀如此大量的資訊。因此需要一個自動形成高品質摘要的機制，來幫助人們以最短的時間獲得最大的知識量。
因此，本論文提出”事件詞彙鏈”的方法，加入了描述文章事件的事件特徵及偵測出文件中事件與概念詞彙關係形成事件詞彙鏈的關聯性計算。透過事件詞彙鏈重要度的計算客觀地判斷事件詞彙鏈的重要性，選擇出重要的事件詞彙鏈來擷取出幫助使用者了解文件重點的摘要。經由實驗發現，以事件詞彙鏈為基礎可有效地改善文件摘要。

Due to the population of the internet, people can access much more information easily than before, which leads to information overload problem. In addition, there exists information redundancy problem. For example, a lot of online electronic news websites are built and many websites may present the same events in different arguments. If the user wants to know the overall picture of the thing, they must spend a lot of time to surf various electronic news website and browse related news. One needs to collect and read all related news in order to obtain the complete information. However, the modern busy people do not have so much time to collect and read the large amount of information. Therefore, it is desirable to have a mechanism to automatically format a high quality summary for helping people receive the maximum amount of knowledge in the shortest time.
In this thesis, we propose a method called “Event Lexical Chain”. Adding the event features which describe the event in the documents and the relation between terms can form the Event Lexical Chain, which can be used to detect the events and concept terms in the documents. The importance of the Event Lexical Chain can be objectively judged by weighting the Event Lexical Chain. Selecting the important Event Lexical Chain can extract the summary to help users understand the key point of the documents. The experimental results reveal that the multi-document based on Event Lexical Chain can effectively improve the summary of documents.

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