在網路新聞論壇中，由於文章內容是由一般使用者自由發佈，即使論壇中有以主題區分討論內容，但討論文章內容中仍可能呈現出多種討論觀點面向，使用者不容易從數量龐大的討論文章中有效瀏覽自己感興趣的觀點文章。本論文研究所提出的方法可對一組新聞論壇文章自動分析萃取出重要的討論觀點面向（以關鍵字表示），且建立出面向的階層架構關係，並對各文章自動判斷其所包含的各個面向，提供使用者可依討論觀點面向進行文章瀏覽。在探勘分析過程中，我們會先由標題字詞選出重要且出現頻率高的字詞作為面向，並對這些面向關鍵字探勘出其相關擴展字詞，接著我們利用向量空間模型分別計算整篇文章所包含的字詞與面向擴展字詞的相關程度，以及文章中各個句子所包含的字詞與面向擴展字詞的相似度，再將這兩個結果合併判斷一篇文章所包含之相關面向。實驗結果顯示：本論文系統對各文章所選定的面向與受試者挑選的面向結果一致性很高；且將多個主題的文章混合在一起時，本論文方法也可以將不同主題的文章所涵蓋的面向正確地萃取出來。

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