現今，因為網路的快速發展，發展出了以使用者為中心的網站，並且提供網站(部落格、論壇、討論區…等)讓使用者分享自己對公司或產品的評價；在這些散布在網路上大量的文章，為了能快速取得文章內之資訊，中文意見探勘系統就為之重要。本論文主要研究中文意見探勘系統之句型文法，分析Mobile01和PTT的電信和網路兩大熱門討論區發文者對公司或產品之文章。我們句型文法主要利用「預設Topic」、「子句優先」和「對應關係」搭配句型來配對意見元素表達發文者意見。實驗結果顯示各月份和不同討論區之準確率、回收率和F1相差不多，顯示我們的句型文法是穩定的；另外在考慮預設Topic情況下，實驗結果顯示對整體之數據是有成效的。 Today, the fast development of the Web has resulted in the user-centric websites and websites (blog, forum, BBS, etc) that allow users to share their comments on a company or a product. For the rapid access to information contained in the huge amounts of articles on the Web, the Chinese opinion mining system is very important. This paper discusses the sentence grammar of the Chinese opinion mining system, analyzes the articles on companies or products published on two popular BBS of Mobile01 and PTT telecommunications. Our sentence grammar mainly uses “default topic”, “clause priority” and “corresponding relationship” coupled with sentences to match up with the opinion elements to express the views of the article posters. The experimental results suggest that precision, recall and F1 are the same in various months and BBS, suggesting our sentence grammar is stable. By considering the default topic, the experimental results prove that the proposed method is effective in terms of overall data.
