臺灣博碩士論文加值系統

因為建立或維護詞庫型意見探勘系統，需耗費大量人力或時間，本研究試圖將這些耗費大量人力的工作簡化，原來建立或維護詞庫時需要看很多文章，並挑出針對領域有用的意見詞之後新增至詞庫，現在只要執行演算法將文章內新的意見詞挑出，之後判斷演算法所挑出的新意見詞及比照新意見詞和句子是否為對領域有用的意見詞並新增至詞庫。由於檢查演算法挑出的新意見詞比直接看文章來得省時省力，進而達到降低詞庫建置或維護的成本。

Due to huge manpower and time consuming for establishing and maintaining a word library type Opinion Mining system, the study attempts to simplify the operation of huge manpower and time consuming, thus the original reading many articles for establishing and maintaining the word library, where Opinion Word useful to the domain have to be pickup and added to the word library, with the process of the study, it only needs to execute algorithms to pickup new Opinion Word in articles, then determine whether the pickup Opinion Word is useful to the domain by comparing the pickup Opinion Word and sentence, and then add to word library. Owing to checking new Opinion Word picked out by algorithms is much time and manpower saving comparing to reading articles directly, moreover word library establishing and maintaining cost can be reduced.

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 意見單元定義 7
2.2 特徵詞的抽取與判斷 11
2.3 意見詞的擴充 21
2.4 意見極性判斷 33
第3章 演算法介紹 41
3.1 演算法──斷詞斷字 43
3.2 意見詞極性轉變之處理 52
第4章 實驗討論 57
4.1 資料來源與背景 58
4.2 電信領域實驗結果分析與討論 59
4.3 網路領域實驗結果分析與討論 71
第5章 結論與未來展望 82
附表A 84
附表B 84
附表C 85
附表D 85
參考文獻 86
附錄-英文論文 92

圖目錄
圖 1 共生模式八種類型 13
圖 2 特徵詞與意見詞配對矩陣 18
圖 3 意見詞擴充示意圖 23
圖 4 Feature-Opinion對應圖 38
圖 5 演算法──斷詞斷字步驟 44
圖 6 一段隱含詞庫無法辨識之意見詞的段落 47
圖 7 遺漏意見元素的段落 49
圖 8 遺漏意見元素的段落 49
圖 9 刪除被長詞包含的短詞 51
圖 10 演算法──意見詞加意見詞步驟 54
圖 11 演算法──意見詞不意見詞步驟 55
圖 12 演算法──意見詞了步驟 56
圖 13 演算法執行流程 57
圖 14 各月份意見詞標記所需人工判斷筆數 61
圖 15 演算法──斷詞斷字頻率1以上與頻率2以上所需花費時間(分)對照 64
圖 16 演算法──斷詞斷字頻率2以上各月份所需人工判斷筆數 64
圖 17 演算法──意見詞加意見詞各月份所需人工判斷筆數 66
圖 18 演算法──意見詞不意見詞各月份所產生筆數 68
圖 19 演算法──意見詞了各月份所需人工判斷筆數 70
圖 20 各月份意見詞標記所需人工判斷筆數 73
圖 21 演算法──斷詞斷字頻率1以上與頻率2以上所需花費時間(分)對照 76
圖 22 演算法──斷詞斷字頻率2以上各月份所需人工判斷筆數 76
圖 23 演算法──意見詞加意見詞各月份所需人工判斷筆數 78
圖 24 演算法──意見詞了各月份所需人工判斷筆數 81

表目錄
表 1 意見元素 8
表 2 電影元素的特徵表 13
表 3 特徵詞詞性 17
表 4 意見詞與特徵詞之間的定義 28
表 5 Propagation rule表 29
表 6 「哈啦飆網包」拆解後結果 50
表 7 電信領域各月份資料量 59
表 8 各月份意見詞標記實驗數據 60
表 9 演算法──斷詞斷字實驗數據 63
表 10 演算法──意見詞加意見詞實驗數據 66
表 11 演算法──意見詞不意見詞實驗數據 68
表 12 演算法──意見詞了實驗數據 70
表 13 網路領域各月份資料量 71
表 14 各月份意見詞標記實驗數據 72
表 15 演算法──斷詞斷字實驗數據 75
表 16 演算法──意見詞加意見詞實驗數據 78
表 17 演算法──意見詞不意見詞實驗數據 79
表 18 演算法──意見詞了實驗數據 81

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