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  • 學位論文

以專家導向為基礎的個人化新聞過濾系統

The Development of A Personalized News Filter System Using Expert Oriented Approach

指導教授 : 劉士豪

摘要


由於新聞資訊日漸增多,加上網路傳播的蓬勃發展,已經導致現在的電子新聞數量呈現高度的資訊爆炸,如何找到符合個人需求的內容,控制閱讀的數量與品質,以達真正的有效閱讀,已經成為一個刻不容緩的課題,特別是新聞資訊具有變動性高且充滿隱性需求的特性,所以在過去自動化的分類與過濾的許多研究上均遭到許多的挑戰,包括使用者需求不明確、使用者需求多變、隱性需求不意察覺、系統學習時間過長的問題。 本研究觀察新聞閱讀行為中讀者與新聞專家之間的互動關係,發展出一個以新聞專家為核心的過濾基礎,運用觀察和記錄專家的點閱與推薦以作為新聞的評分標準,並利用Attention.XML的技術作為紀錄與傳播的媒介,將專家每次閱讀的評分紀錄散播給訂閱的讀者。 在經過實際的驗證後,發現透過專家導向的新聞過濾系統,可以依據專家所提供的新聞評分內容與本研究提出的權重計算方式,產生各種過濾後的新聞內容,提供讀者一份更符合需求的個人化新聞內容,進而增加新聞閱讀的品質與效率。

並列摘要


As more and more news and information, have led to the electronic media has become highly quantity of the information explosion. How to find the useful news for reader is an important discussion. This study develops a personalized news filter system to recommend the personalized news content. The system using expert oriented approach, it collect the experience of news expert and share the experience to news reader. By the system, readers can choose the different experts for their likes. After the empirical test, this study finds that “the Personalized News Filtering System” can make a good matching performance for news reader. Most members are satisfied with the recommendation in the personalized e-news. Beside, it helps the internet news to create the added value for readers.

參考文獻


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