因為網際網路的快速發展，廠商與消費者可以從網路上獲得具有參考價值的評論文章，但是，閱覽許多文章非常耗費時間，這也是本研究要改善的方向。
本研究建置一套中文意見探勘系統，針對特定領域進行分析，本論文運用演算法對論壇網站Mobile01上的電信領域文章進行分析，同時搭配人工針對演算法結果進行意見詞的標記工作，以提高意見詞的正確性，並提供分析圖表，使User可快速取得正確且客觀的資訊。

In the wake of rapid internet developing, review articles of reference value can be obtained from networks by both makers and consumers, however, the reading of the massive articles becomes very time consuming, and this is what the study aims at. 
The study established a Chinese opinion mining system, where algorithms were employed specific to special domain, analysis conducted, meanwhile matched with manual markup job for opinion words on algorithm results, to enhance accuracy of opinion words, and provide analysis diagrams, so that accurate and objective information can be obtained by users rapidly.

目錄
第一章	序論	- 1 -
1.1.	研究動機與目的	- 1 -
1.2.	論文架構	- 3 -
第二章	文獻探討	- 4 -
2.1.	意見單元定義	- 4 -
2.2.	特徵詞的抽取與判斷	- 8 -
2.2.1.	人工建立特徵詞詞庫	- 9 -
2.2.2.	使用自然語言技術截取特徵詞	- 11 -
2.3.	意見詞的擴充	- 17 -
2.3.1.	利用詞庫擴充意見詞	- 17 -
2.3.2.	利用語料庫擴充意見詞	- 20 -
2.3.3.	半自動化系統	- 26 -
2.4.	意見極性判斷	- 29 -
2.4.1.	判斷意見詞傾向	- 29 -
2.4.1.1.	利用統計計算意見傾向	- 30 -
2.4.1.2.	特徵詞和意見詞之間的對應關係	- 32 -
2.4.2.	否定詞和連接詞的判斷	- 34 -
2.5.	意見探勘系統	- 36 -
2.5.1.	英文意見探勘系統	- 36 -
2.5.1.1.	Opinion Observer	- 36 -
2.5.1.2.	IBM WebFountain	- 38 -
2.5.1.3.	RevMiner	- 40 -
2.5.2.	中文意見探勘系統	- 43 -
2.5.2.1.	CopeOpi	- 43 -
2.5.2.2.	Chien-Liang’s work	- 45 -
第三章	研究方法	- 46 -
3.1.	問題陳述	- 46 -
3.2.	系統設計	- 48 -
3.2.1.	系統架構	- 48 -
3.2.2.	演算法運算流程	- 50 -
3.2.3.	分析報表規則設計與處理	- 52 -
3.2.3.1.	Topic分析	- 53 -
3.2.3.2.	Feature/產品分析	- 55 -
3.2.3.3.	異常評價分析	- 57 -
3.2.3.4.	雷達圖分析	- 58 -
第四章	研究探討	- 59 -
4.1.	環境設置	- 59 -
4.2.	使用者介面	- 62 -
4.2.1.	執行演算法流程	- 62 -
4.2.1.1.	「意見詞標記」演算法	- 63 -
4.2.1.2.	「斷詞斷字」演算法	- 66 -
4.2.1.3.	「Opinion Word加Opinion Word」演算法	- 69 -
4.2.1.4.	「Opinion Word不Opinion Word」、「意見詞了」演算法	- 71 -
4.2.2.	執行報表分析流程	- 74 -
4.2.2.1.	「Topic分析」介面	- 74 -
4.2.2.2.	「Feature/產品分析」介面	- 76 -
4.2.2.3.	「異常評價分析」介面	- 79 -
4.2.2.4.	「雷達圖分析」介面	- 81 -
第五章	結論	- 83 -
參考文獻	- 84 -
附錄-英文論文	- 89 -

圖目錄
圖1 共生模式八種類型	- 10 -
圖2 特徵詞與意見詞配對矩陣	- 14 -
圖3 意見詞擴充示意圖	- 18 -
圖4 在汽車領域中半自動標註與人工標註的比較	- 28 -
圖5 在遊戲領域中半自動標註與人工標註的比較	- 28 -
圖6 Feature-Opinion對應圖	- 34 -
圖7 Opinion Observer的比較畫面	- 37 -
圖8 人工標註系統畫面	- 38 -
圖9 WebFountain GUI 經過意見分析後的產品比較圖	- 39 -
圖10 WebFountain可以讓使用者選擇產品以及來源	- 39 -
圖11 ReMiner在手機上根據特徵分類(Common圖)	- 40 -
圖12 Special圖	- 41 -
圖13 Cloud圖	- 42 -
圖14 Categories 圖	- 42 -
圖15 CopeOpi使用者選擇畫面	- 44 -
圖16 各個時間趨勢	- 44 -
圖17 包含主題的文章	- 44 -
圖18 可選擇有關的電影以及特徵,並且知道正負傾向評論等級	- 45 -
圖19 系統架構圖	- 48 -
圖20 演算法流程圖	- 50 -
圖21 系統統計分析示意圖	- 52 -
圖22 Topic分析報表流程圖	- 53 -
圖23 Feature/產品分析流程圖	- 55 -
圖24 異常評價分析流程圖	- 57 -
圖25 雷達圖分析流程	- 58 -
圖26 Microsoft SQL Server Management Studio管理介面	- 60 -
圖27 Apache Tomcat Server console介面	- 60 -
圖28 中文意見探勘系統登入頁面	- 61 -
圖29 演算法詞彙管理功能頁面	- 62 -
圖30 演算法詞彙管理功能頁面	- 63 -
圖31 「意見詞標記」演算法結果編輯頁面(一)	- 64 -
圖32 「意見詞標記」演算法結果編輯頁面(二)	- 65 -
圖33 意見詞與Feature對應關係編輯頁面	- 66 -
圖34 「斷詞斷字」演算法結果編輯頁面	- 68 -
圖35 意見詞(或名詞)與Feature對應關係編輯頁面	- 68 -
圖36 「Opinion Word加Opinion Word」演算法結果編輯頁面	- 70 -
圖37 意見詞與Feature對應關係編輯頁面	- 70 -
圖38 「意見詞了」演算法結果編輯頁面	- 72 -
圖39 意見詞與Feature對應關係編輯頁面	- 73 -
圖40 意見詞與Feature對應關係編輯頁面	- 73 -
圖41 Topic評價分析頁面	- 75 -
圖42 Topic評價分析之直條圖	- 75 -
圖43 Topic評價分析之摺線圖	- 76 -
圖44 Topic評價分析之圓餅圖	- 76 -
圖45 Feature/產品分析頁面	- 77 -
圖46 Feature/產品分析直條圖	- 78 -
圖47 Feature/產品分析摺線圖	- 78 -
圖48 Feature/產品分析圓餅圖	- 79 -
圖49 異常評價分析頁面	- 80 -
圖50 異常評價分析直條圖(一)	- 80 -
圖51 異常評價分析直條圖(二)	- 81 -
圖52 雷達圖分析	- 82 -

表目錄
表 1 意見元素	- 5 -
表 2 電影元素的特徵表	- 10 -
表 3 特徵詞詞性	- 13 -
表 4 意見詞與特徵詞之間的定義	- 22 -
表 5 Propagation rule表	- 24 -

[1]	P. D. Turney, "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews," presented at the Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Philadelphia, Pennsylvania, 2002.
[2]	M. Hu and B. Liu, "Mining and summarizing customer reviews," presented at the Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, Seattle, WA, USA, 2004.
[3]	L.-W. Ku and H.-H. Chen, "Mining opinions from the Web: Beyond relevance retrieval," Journal of the American Society for Information Science and Technology, vol. 58, pp. 1838-1850, 2007.
[4]	N. Kobayashi, K. Inui, and Y. Matsumoto, "Opinion Mining from Web Documents: Extraction and Structurization," Information and Media Technologies, vol. 2, pp. 326-337, 2007.
[5]	S.-M. Kim and E. Hovy, "Determining the sentiment of opinions," presented at the Proceedings of the 20th international conference on Computational Linguistics, Geneva, Switzerland, 2004.
[6]	B. Liu and L. Zhang, "A Survey of Opinion Mining and Sentiment Analysis
Mining Text Data," C. C. Aggarwal and C. Zhai, Eds., ed: Springer US, 2012, pp. 415-463.
[7]	B. Liu, M. Hu, and J. Cheng, "Opinion observer: analyzing and comparing opinions on the Web," presented at the Proceedings of the 14th international conference on World Wide Web, Chiba, Japan, 2005.
[8]	G. A. Miller. (1980). WordNet. Available: http://wordnet.princeton.edu/
[9]	P. J. Stone, D. C. Dunphy, and M. S. Smith, "The General Inquirer: A Computer Approach to Content Analysis," 1966.
[10]	A. Esuli and F. Sebastiani, "Sentiwordnet: A publicly available lexical resource for opinion mining," 2006, pp. 417-422.
[11]	B. Ohana and B. Tierney, "Sentiment classification of reviews using SentiWordNet," in 9th. IT & T Conference, 2009, p. 13.
[12]	 General  Inquire. Available: http://www.wjh.harvard.edu/~inquirer/
[13]	A. Esuli and F. Sebastiani, "Determining term subjectivity and term orientation for opinion mining," 2006, pp. 193-200.
[14]	A. Andreevskaia and S. Bergler, "Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses," 2006, pp. 209-216.
[15]	L. Zhuang, F. Jing, and X.-Y. Zhu, "Movie review mining and summarization," presented at the Proceedings of the 15th ACM international conference on Information and knowledge management, Arlington, Virginia, USA, 2006.
[16]	董振東, "HowNet," 1999 
[17]	T. Peiliang, L. Yuanchao, L. Ming, and Z. Shanzong, "Research of Product Ranking Technology Based on Opinion Mining," in Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on, 2009, pp. 239-243.
[18]	S. Bin and C. Kuiyu, "Mining Chinese Reviews," in Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on, 2006, pp. 585-589.
[19]	杨锋, 彭勤科, and 徐涛, "基于随机网络的在线评论情绪倾向性分类," 自动化学报, vol. 36, pp. 837-844, 2010.
[20]	李林琳, "基于特定领域的汉语句子意见挖掘," 上海交通大学, 2008.
[21]	娄德成 and 姚天昉, "汉语句子语义极性分析和观点抽取方法的研究," 计算机应用, vol. 26, pp. 2622-2625, 2006.
[22]	L.-W. Ku, H.-W. Ho, and H.-H. Chen, "Opinion mining and relationship discovery using CopeOpi opinion analysis system," Journal of the American Society for Information Science and Technology, vol. 60, pp. 1486-1503, 2009.
[23]	陳立, "中文情感語意自動分類之研究," 2010.
[24]	楊盛帆, "以整合式規則來做網路論壇上的 3C 產品口碑分析," 元智大學資訊管理學系研究所碩士論文, 2009.
[25]	孫瑛澤, 陳建良, 劉峻杰, 劉昭麟, and 蘇豐文, "中文短句之情緒分類," 2010.
[26]	謝鎮宇, "意見探勘在中文評鑑語料之應用," 交通大學資訊學院碩士在職專班資訊組學位論文, 交通大學, 2010.
[27]	H. Xu, K. Zhao, L. Qiu, and C. Hu, "Expanding Chinese sentiment dictionaries from large scale unlabeled corpus," 2011.
[28]	S. Tan, Y. Wang, and X. Cheng, "Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples," presented at the Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore, Singapore, 2008.
[29]	P. Turney and M. L. Littman, "Measuring praise and criticism: Inference of semantic orientation from association," 2003.
[30]	H. Kanayama and T. Nasukawa, "Fully automatic lexicon expansion for domain-oriented sentiment analysis," presented at the Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, Sydney, Australia, 2006.
[31]	G. Qiu, B. Liu, J. Bu, and C. Chen, "Expanding domain sentiment lexicon through double propagation," 2009, pp. 1199-1204.
[32]	G. Qiu, B. Liu, J. Bu, and C. Chen, "Opinion Word Expansion and Target Extraction through Double Propagation," Computational Linguistics, vol. 37, pp. 9-27, 2011/03/01 2011.
[33]	A.-M. Popescu and O. Etzioni, "Extracting product features and opinions from reviews," presented at the Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada, 2005.
[34]	Q. Mei, X. Ling, M. Wondra, H. Su, and C. Zhai, "Topic sentiment mixture: modeling facets and opinions in weblogs," presented at the Proceedings of the 16th international conference on World Wide Web, Banff, Alberta, Canada, 2007.
[35]	Z. Zhai, B. Liu, L. Zhang, H. Xu, and P. Jia, "Identifying evaluative sentences in online discussions," 2011.
[36]	N. Kobayashi, K. Inui, Y. Matsumoto, K. Tateishi, and T. Fukushima, "Collecting Evaluative Expressions for Opinion Extraction
Natural Language Processing – IJCNLP 2004." vol. 3248, K.-Y. Su, J. i. Tsujii, J.-H. Lee, and O. Kwong, Eds., ed: Springer Berlin / Heidelberg, 2005, pp. 596-605.
[37]	M. Fuketa, Y. Kadoya, E. Atlam, T. Kunikata, K. Morita, S. Kashiji, et al., "A method of extracting and evaluating good and bad reputations for natural language expressions," International Journal of Information Technology & Decision Making, vol. 4, pp. 177-196, 2005.
[38]	A. Esuli and F. Sebastiani, "Determining the semantic orientation of terms through gloss classification," presented at the Proceedings of the 14th ACM international conference on Information and knowledge management, Bremen, Germany, 2005.
[39]	C. Zhang, D. Zeng, J. Li, F.-Y. Wang, and W. Zuo, "Sentiment analysis of Chinese documents: From sentence to document level," J. Am. Soc. Inf. Sci. Technol., vol. 60, pp. 2474-2487, 2009.
[40]	L. Zhuang, F. Jing, and X. Y. Zhu, "Movie review mining and summarization," 2006, pp. 43-50.
[41]	邱鴻達, "意見探勘在中文電影評論之應用," 國立交通大學	資訊科學與工程研究所, 2011.
[42]	梅家駒等編著, 同義詞詞林, 1983.
[43]	X. Ding, B. Liu, and P. S. Yu, "A holistic lexicon-based approach to opinion mining," 2008, pp. 231-240.
[44]	Q. Su, X. Xu, H. Guo, Z. Guo, X. Wu, X. Zhang, et al., "Hidden sentiment association in chinese web opinion mining," presented at the Proceedings of the 17th international conference on World Wide Web, Beijing, China, 2008.
[45]	V. Hatzivassiloglou and K. R. McKeown, "Predicting the semantic orientation of adjectives," 1997, pp. 174-181.
[46]	Y. Qiang, S. Wen, and L. Yijun, "Sentiment Classification for Movie Reviews in Chinese by Improved Semantic Oriented Approach," in System Sciences, 2006. HICSS '06. Proceedings of the 39th Annual Hawaii International Conference on, 2006, pp. 53b-53b.
[47]	L. W. Ku, I. C. Liu, C. Y. Lee, K. Chen, and H. H. Chen, "Sentence-Level Opinion Analysis by CopeOpi in NTCIR-7," 2008.
[48]	P. Ting-Chun and S. Chia-Chun, "Using Chinese part-of-speech patterns for sentiment phrase identification and opinion extraction in user generated reviews," in Digital Information Management (ICDIM), 2010 Fifth International Conference on, 2010, pp. 120-127.
[49]	K. Dave, S. Lawrence, and D. M. Pennock, "Mining the peanut gallery: opinion extraction and semantic classification of product reviews," presented at the Proceedings of the 12th international conference on World Wide Web, Budapest, Hungary, 2003.
[50]	M. Gamon, A. Aue, S. Corston-Oliver, and E. Ringger, "Pulse: Mining Customer Opinions from Free Text
Advances in Intelligent Data Analysis VI." vol. 3646, A. Famili, J. Kok, J. Pena, A. Siebes, and A. Feelders, Eds., ed: Springer Berlin / Heidelberg, 2005, pp. 741-741.
[51]	T. Wilson, P. Hoffmann, S. Somasundaran, J. Kessler, J. Wiebe, Y. Choi, et al., "OpinionFinder: a system for subjectivity analysis," presented at the Proceedings of HLT/EMNLP on Interactive Demonstrations, Vancouver, British Columbia, Canada, 2005.
[52]	J. Huang, O. Etzioni, L. Zettlemoyer, K. Clark, and C. Lee, "RevMiner: an extractive interface for navigating reviews on a smartphone," presented at the Proceedings of the 25th annual ACM symposium on User interface software and technology, Cambridge, Massachusetts, USA, 2012.
[53]	J. Yi and W. Niblack, "Sentiment mining in WebFountain," in Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on, 2005, pp. 1073-1083.
[54]	L. Chien-Liang, H. Wen-Hoar, L. Chia-Hoang, L. Gen-Chi, and E. Jou, "Movie Rating and Review Summarization in Mobile Environment," Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 42, pp. 397-407, 2012.