延伸標記語言(eXtensible Mark-up Language, XML) 規格是由全球資訊網標準製定組織(W3C) 制定，並於 1998 年 2 月成為推薦規格。XML已逐漸成為網路上不同系統和資料庫間資訊交換的新標準，加上其結構化的特性，使得在處理大量XML文件分類成為一重要課題。目前XML在文件分類上有利用Naïve Bayes演算法、樣版辨識和影像處理分割技術、詞性標記和法則式技術以及TFIDF以解決分類問題等方法，由於過去的研究鮮少針對文件本身的內容作分析，可能造成含糊文件或衍生的相關文件無法正確分類。本研究先以文件的樹狀結構特性找出每個項目的重要性等級，並利用TFIDF方法取得特徵項目後，便可藉由比對各類別的特徵項目將文件正確分類。在分類過程中，同時考量文件中的重要新詞以提高分類正確率。為使分類器能不侷限在限有特徵項目中，本研究也提出一加入重要特徵項目的機制，使分類器能適應廣泛內容的文件。本研究最後與同樣使用階層特性的XML文件分類方法作一比較，結果顯示本研究能顯著改善分類之正確率。

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