在最近幾年的研究當中，關於網頁內容的研究數量相當的多。對於網站上的意見分析也顯得越來越重要。人們在網路上對於某個產品的評價對於我們在網路上購物或者下決策時是相當重要的參考依據。舉例來說，一個在網路上的使用者在選擇要入住哪家旅館時，通常會透過參考入口網站中有關於使用者想比較的旅館的意見來做為決定的因素。因此，在本篇論文當中，我們使用了自然語言處理以及資料探勘中的技巧來分析入口網站中的網頁並擷取出有關於擷取的網頁的旅館的特徵，並將每一個特徵透過搜尋引擎來計算特徵的分數。並且設計了一個線上的系統，讓使用者可以透過我們的介面來做比較。相信透過這樣的方式，使用者在比較網頁中大量的意見時可以更清楚、簡單、直覺的比較並更快速的做出決定。

In recent years, a considerable of number of studies have been conducted on the effects of comments on the web. People’s appraisal has high confidence to express their behaviors and aspects. Thus, the appraisals on the web are significant information for customer making their decision. For instance, people could select the best hotel according to the existing appraisals on the web. In this paper, we are concerned with the difference between reviews of products. An unsupervised learning approach can model this information perfectly. Furthermore, we simply combined the data mining with natural language processing techniques to extract features from a large of appraisals. For each feature, we generalized a corresponding appraisal by using probabilistic measure and we designed a web interface to let user compare online. We adopted the Hotel information that was collected form Yahoo as our dataset. Lastly, our comparative results were clearly represented in a visual way.

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