隨著網際網路的快速發展影響了人們獲取資訊的方式，傳統透過報紙、廣播接觸新聞的讀者不斷減縮，取而代之的是線上新聞文章，越來越多的讀者透過電腦或行動裝置來瀏覽新聞，因此新聞媒體產業也開始走向數位化，各家新聞媒體透過網頁發布線上新聞文章，傳遞資訊給群眾。網路上大量的新聞文章固然可以帶給讀者多樣化的新聞，但同時讀者也需要耗費許多時間閱覽才能夠消化資訊。此外新聞的事件期間，隨著時間發展或話題的延燒經常是持續一段時間的，當讀者欲針對特定事件做檢索了解事件發生的來龍去脈時，利用當前新聞網站的搜尋功能做查詢，而搜尋的結果往往面對的是大量新聞文章，導致讀者須要花費更多心力逐一檢視、整理，才能獲取真正尋求的資訊。
面對上述問題，有些平台應用內容策展(Content Curation)的概念，將大量的新聞文章根據事件、議題為基礎進行彙整，經由選材、精煉、組織並增加價值等步驟處理並呈現給讀者。有別於以往內容策展平台經由編輯人工進行整理之方式，本研究主要以自動化實做新聞事件之內容策展，首先萃取出資料集的主題，並透過隱馬爾可夫模型利用字詞序列找出主題轉移之序列，接著計算主題強度以及強度之變異偵測出事件發展期間重要的時間點，最終產生簡潔的文章摘要，結合時序化與摘要兩項特點，來設計呈現給讀者的事件策展結果，期望能有效幫助讀者簡單明瞭的閱讀並快速地掌握事件的脈絡。

The read habit of readers have changed, more and more readers use the computers or mobile devices to browse news, and the news industry is also digitized. Various news broadcaster published online news to pass information. A large number of online news bring readers a variety of information, but at the same time, readers also need to spend more time digesting them. When readers quering a news event, it often returns a large number of search result, which leads readers to spend extra effort to sort out.
In order to solve the problem, some platforms apply the concept of Content Curation, which aggregates the news articles based on event, and then organize and present to readers. At present, most of Content Curation is manually organized. Different from the way of the past platform, this study proposes an automated method of news curation. We first extract the topics from the dataset and use the word sequence to find out the topic sequence through the Hidden Markov Model. Then calculate the strength and the variation to detect important time points during the development of the event. Finally, generate a concise summary to every time points. We combine chronology and summary to design the curation, and look forward to help readers to quickly grasp the context of the news event.
Experiments has found that the method has a good performance in each modules. The curation result have good practicality for the readers. But in terms of coherence, there is slightly insufficient to improve.

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