現在上網發文、爬文，以及查找資料等行為，儼然而成現代人的生活習慣。搜尋結果往往不考慮與使用者需求契合的程度，只要關鍵字曾出現在標題或內文，就會被當作相關資料回覆給使用者，故關鍵字搜尋的結果可能含有無相關的資料。
鑑於一般關鍵字搜尋的方式，其回覆結果可能摻雜不相關的資料，有礙編輯人員的工作效率及產出比，故本研究提出改善並優化關鍵字搜尋的方式，以減少不相關的文章產生，並針對特定主題或領域優化關鍵字的搜尋方式。

Nowadays, we use keywords to perform searches when sending texts, crawling the Net and finding data on the Internet, but the search engine does not consider the degree of matching with the user's needs. In other words, the general keyword search method works in a way that as long as the keyword appears in the titles or texts of articles, they will appear on the screen as relevant data. Therefore, the results of the keyword search may contain no relevant data. As a result, this study proposes a way to improve and optimize keyword search to reduce irrelevant articles and optimize keyword search for specific subjects or domains.

目錄
第1章 緒論 1
1.1 研究動機與目的 1
1.2 研究架構 6
第2章 文獻探討 7
2.1 中文意見探勘系統相關研究 7
2.2 本研究室開發的中文意見探勘系統簡介 11
第3章 研究方法 15
3.1 問題陳述 15
3.1.1 新聞網站 15
3.1.2 論壇 20
3.2 關鍵字搜尋演算法 22
3.2.1 排除關鍵字類型 22
3.2.2 新聞網站處理方式 26
3.2.3 論壇處理方式 28
第4章 分析實例 31
4.1 系統架構與環境 31
4.2 資料來源 34
4.3 實驗結果 36
4.3.1 關鍵字搜尋優化實例-以新聞為例 36
4.3.2 關鍵字搜尋優化實例-以論壇為例 42
第5章 結論 44
參考文獻	45
附錄 51

圖目錄
圖1 中文意見探勘系統架構圖 12
圖2 文章下載與配置流程圖 13
圖3 中文意見探勘系統文章分析流程圖 14
圖4 中嘉寬頻與其他不相關的新聞 範例3-1 17
圖5 新竹社會處與其他不相關的新聞 範例3-2 18
圖6 資料來源之不相關文章圖例 19
圖7 新增排除句關鍵字介面 24
圖8 排除句關鍵字 設定 25
圖9 新聞網站關鍵字搜尋演算法 26
圖10 論壇關鍵字搜尋演算法 28
圖11 系統架構圖 32
圖12 系統執行流程圖 33
圖13 新聞頻道爬文收集新聞筆數比例圖 36
圖14 2018/04/01至2018/04/07之關鍵字訓練與篩選相關文章筆數關係折線圖	38
圖15 2018/04/08至2018/04/14之關鍵字訓練與篩選相關文章筆數關係折線圖	39
圖16 2018/04/15至2018/04/21之關鍵字訓練與篩選相關文章筆數關係折線圖	39
圖17 2018/04/22至2018/04/28之關鍵字訓練與篩選相關文章筆數關係折線圖	40
圖18 2018/04/29至2018/05/05之關鍵字訓練與篩選相關文章筆數關係折線圖	40
圖19 2018/05/06至2018/05/12之關鍵字訓練與篩選相關文章筆數關係折線圖	41
圖20 2018/05/13至2018/05/19之關鍵字訓練與篩選相關文章筆數關係折線圖	41
圖21 2018/05/20至2018/05/26之關鍵字訓練與篩選相關文章筆數關係折線圖	42
圖22 2018/05/27至2018/06/02之關鍵字訓練與篩選相關文章筆數關係折線圖	42
圖23 不相關文章被收集之案例 43

表目錄
表1 關鍵字與標題對照表 21

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