整合自動摘要技術於中文新聞RSS閱讀器之研究

Abstract

在現今數位化時代中，智慧型手機的普及率高，隨身攜帶手機上網看新聞是大多數人的生活習慣，手機上看新聞非常即時便利，但顯示器畫面較小，無法將新聞全文傳送到手機上，而使用RSS Reader看新聞則成為最方便的新聞內容訂閱方式。 大多數RSS Feed內的新聞摘錄都取用新聞的前幾句，並且當訂閱多家新聞頻道時，會有新聞洗版的情況，如何從眾多的新聞之中篩選出自己需要的、喜愛的新聞乃是一個值得關注的議題。 本研究提出一套有別於傳統新聞瀏覽器的自動化新聞摘要系統，以國內兩大線上中文新聞發行者的RSS新聞為例，將新聞全文取回並透過CKIP 的斷詞切字處理後，利用MEAD中的主題偵測與追踪技術將新聞分群，以過濾重複的新聞文章，避免新聞洗版問題；再利用多文件摘要技術，為同一個新聞主題群內的所有新聞擷取摘要、萃取其精華，以適合行動瀏覽。 最後，本研究再設計一符合行動瀏覽的應用程式，讓使用者在閱讀新聞時，不論其使用的是智慧型手機或平板電腦上，皆有一致性的瀏覽體驗。

In the modern digital era, due to the prevalence of smart phones, it has become a habit of most people to read news on their mobile phones. Despite the convenience of reading news on mobile phones, the small display is unable to show the full content of each news article. RSS Reader is a solution that allows people to subscribe and read news on mobile devices in the easiest way. Most RSS feeds contain the first few lines of each news article. However, when users subscribe to numerous news channels, news of hot topics may easily take up the entire page of their RSS readers. Therefore, how to filter news based on user preference is an important issue. This study proposed a novel automatic news summarization system for RSS readers. Using the two major Chinese RSS feeds channels in Taiwan as an example, this system retrieved full news articles, processed them using the CKIP Chinese word segmentation technology, and then clustered news based on the topic detection and tracking techniques of MEAD to filter out repetitive news articles. Finally, a multi-document summarization technique was applied to summarize news articles in each topic cluster for optimal viewing on mobile V devices. Finally, this study introduced a mobile RSS reader application that enables users to have a consistent viewing experience across all kinds of smart phones and Tablet PCs.