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系統識別號 U0026-0812200911404162
論文名稱(中文) 情緒實體論半自動建構及其在情緒辨識上之應用
論文名稱(英文) Semi-Automatic Construction of Affection Ontology and Its Application on Emotion Identification
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 93
學期 2
出版年 94
研究生(中文) 陳如婷
研究生(英文) Ru-Ting Chen
學號 P7692401
學位類別 碩士
語文別 英文
論文頁數 120頁
口試委員 指導教授-郭淑美
口試委員-蔣榮先
口試委員-孫光天
口試委員-謝文雄
指導教授-郭耀煌
中文關鍵字 模糊推論  數位家庭  情緒辨識  情緒實體論  詞組計算分析 
英文關鍵字 Fuzzy Inference  Affection Ontology  Pattern Computing Analysis  Digital home  Emotion Identification 
學科別分類
中文摘要   數位家庭(Digital Home)已被廣泛的探討,其應用更是不勝枚舉,而本論文更著重於情緒辨識這個領域。達到情緒辨識可發展的應用層面相當的廣泛,不論在遠距互動教學、提供家庭式即時服務、線上遊戲人物可模擬真實情緒等。而實體論(Ontology)在許多的應用層面上佔很重的份量,舉凡在資訊系統、知識管理及語意網(Semantic Web)。基於實體論的優點,在本論文中,我們提出一個以情緒實體論作為輔助來達成情緒辨識的應用。實體論的建構是一項耗時龐大的工程,有鑑於此,本論文中提出一個半自動建構情緒實體論的方式,在建構情緒實體論方面,先參考 HowNet 初步建立一個雛型的情緒實體論,再採用自我組織映射圖網路將相似的概念(Concept) 和實體(Instance) 聚集在一起,視為實體論的概念和實體,再利用資料探勘的技術找出詞與詞之間的關係(Association),最後再人工調整這個情緒實體論。在情緒辨識之應用方面,利用參考人工標好的關鍵詞向量值來分析詞組,並考量修飾字來加重或減輕此向量,另一方面,再參考半自動建構之情緒實體論對該文章作模糊推論,由分析詞組所得的情緒向量和模糊推論所得的情緒向量總結成代表此單篇文章的情緒向量值,以此情緒向量值作為該文件的分類依據。經由實驗驗證,此方法能有效的分類單篇文章。
英文摘要  The idea of the digital home has been discussed more often in recent years, as services, entertainment and appliance have become more integrated in home networks. The applications in a digital home can include context-awareness, location-awareness, emotion recognition, etc. Our thesis emphasizes the application of emotion identification. The related applications are online remote tutoring, home services, animated movies by training emotional talking heads of virtual actors, and so on. Ontology plays an important role in many information systems, knowledge management systems, and semantic web. Therefore, we propose an application for emotion identification based on an affection ontology. The construction of ontology is a difficult and time-consuming task, so in this thesis we propose a method to semi-automatically construct an affection ontology. First, we construct a prototype of affection ontology with the support of HowNet. Second, we automatically construct an affection ontology using Natural Language Processing, Data Mining, and Neural Network techniques. In the application of emotion identification, we identify which primary emotion an informal essay belongs to by Pattern Computing Analysis and Fuzzy Inference Analysis. The experimental results show our approach can effectively construct an affection ontology and provide an application for emotion identification based on the affection ontology constructed.
論文目次 Contents
List of Figures............................................................VI
List of Tables.............................................................VII
Chapter 1 Introduction......................................................1
1.1 Motivation and Research Contributions.............................1
1.2 Overview of Research on Emotion Identification....................3
1.3 Thesis Organization...............................................4
Chapter 2 Related Works....................................................5
2.1 Survey of Psychological Theory....................................5
2.2 Survey of Ontology ................................................8
2.3 Survey of Ontology Construction...................................11
2.4 Survey of Emotion Identification in Text..........................12
Chapter 3 Semi–Automatic Construction of Affection Ontology...............14
3.1 Prototype Construction of Affection Ontology......................15
3.2 Refinement of Affection Ontology..................................16
3.3 Evaluation of Affection Ontology..................................28
Chapter 4 Application on Emotion Identification in Text....................29
4.1 Document Preprocessing............................................31
4.2 Emotion Identification by Pattern Computing.......................32
4.3 Emotion Identification by Fuzzy Inference.........................40
4.4 Emotion Identification in Text....................................50
Chapter 5 Application on Emotion Identification from Multiple Sources......55
5.1 Emotion Identification from the Informal Essay....................57
5.2 Emotion Identification from Facial Information....................57
5.3 Emotion Identification from the Acoustic Information..............71
5.4 Emotion Identification from Multiple Sources......................78
Chapter 6 Experimental Results and Analysis................................81
6.1 The Results of Semi-Automatic Construction of Affection Ontology..81
6.2 The Results of Emotion Identification from the Informal Essays....93
6.3 The Results of Emotion Identification from Multiple Sources.......108
Chapter 7 Conclusions and Future Research..................................110
7.1 Conclusions.......................................................110
7.2 Future Research...................................................112
References.................................................................113
Appendix A. Conceptual Structure in CKIP (Modified for Affection Domain)...119
Biography ..................................................................120
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