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研究生:蘇韻玲
研究生(外文):Ying-Ling Su
論文名稱:電腦自動分析學術論文摘要中文步的結構及其教學上的應用
論文名稱(外文):Computational Analysis of Move Structures in Computer Science Article Abstracts and Pedagogical Applications
指導教授:張俊盛張俊盛引用關係
指導教授(外文):Jason S. Chang
學位類別:碩士
校院名稱:國立清華大學
系所名稱:資訊系統與應用研究所
學門:電算機學門
學類:系統設計學類
論文種類:學術論文
論文出版年:2005
畢業學年度:94
語文別:英文
論文頁數:94
中文關鍵詞:摘要文步結構搭配詞索引典
外文關鍵詞:abstractmove structurecollocationconcordancer
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摘要
  在本篇論文中我們提出一種方法,以經由電腦自動分析學術論文摘要中文步(move)的結
構,並且驗證敘述其教學上的應用。這種方法利用從網路上自動收集的大量摘要,作為統計
分析、自動學習之用,不同於以往侷限於少量資料的人工分析的研究方法。
  研究過程中,我們只針對一小部分摘要中的各個句子及少量的搭配詞(collocation)做文
步的人工標記。爾後,讓電腦自動學習在大量未加標記的摘要中,學習搭配詞與文步之間的
關係,以擴充實現文步的搭配詞。我們利用已標記文步的摘要及搭配詞,訓練一個產生摘要
的馬可夫模型, 以進行對摘要的自動文步分析。我們也建立一個論文詞彙索引典
(concordancer), CARE。這個查詢系統可以讓英文非母語的學習者,查詢人工或自動標記文
步的論文,幫助其學術論文的寫作。
  獨立的評估顯示我們的自動方法,可提供高精確率的文步標記; 另外,教學上顯示具有
許多詞彙、片語及文步結構的CARE系統,確實能提升英文非母語的學習者,對學術論文摘要
的文步結構的瞭解。總而言之,我們的方法結合了計算分析的架構和資源,有極大的潛力,
可以應用在網路化的電腦輔助學術論文寫作。
關鍵詞:學術論文寫作、摘要、文步結構、搭配詞、索引典
ABSTRACT
This paper introduces a method for computational analysis of move structures in abstracts of
research articles and presents its pedagogical applications.
In our approach, sentences in a given abstract are analyzed and labeled with a specific move in
the light of various linguistic features. The method involves automatically gathering a large number
of abstracts from the Web, manually assigning tags to sentences in a small set of the abstracts as
well as to collocations extracted from abstracts, and automatically learning the relationships among
words and move and the Markov model of move sequences.
These phraseological and inter-move relationships are eventually used to label sentences of
abstracts gathered from the Web. According to these labeled sentences, we present a prototype
concordancer, CARE, which exploits the move-tagged abstracts in a digital environment.
Independent evaluation on a set of real abstracts shows that the move-tagging method performs
with high precision. Pedagogical trials show that the concordancer enriched with words, phrases
and moves significantly enhance non-native speakers’ understanding of well-structured abstracts in
writing.
Our methodology clearly integrates computational, analytical framework and resources, leading
to new ways of Web-based computer-assisted academic writing.
Key words: Academic Writing, Abstract, Move Structure, Collocation, Concordancer
Table of Contents

摘要 i
ABSTRACT ii
Acknowledgement iii
Table of Contents iv
List of Figures vi
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation 1
1.3 Organization of the Thesis 3
Chapter 2 Related Work 4
2.1 Macrostructure of Information in RAs 4
2.2 Rhetorical Structure of Abstracts in RAs 6
2.3 Phraseological Components in Abstracts 7
2.4 Computerized Corpus Analysis of Moves 8
2.5 Summary 9
Chapter 3 Method 10
3.1 Problem Statement 10
3.2 Procedure of Learning One Move per Sentence 11
3.2.1 Acquiring Abstracts for Training 11
3.2.2 Hand-tagging of Seed Abstracts with Moves 14
3.2.3 Extracting Collocations from A 16
3.2.4 Labeling Each Distinct Collocation with One Move 20
3.2.5 Automatically Expanding Collocations for Moves 21
3.2.6 Building a Hidden Markov Model for Move Tagging 25
3. 3 Run Time Automatic Move-tagging 27
3.3.1 Pre-processing 27
3.3.2 Extracting Collocations from TD 28
3.3.3 Automatically Identifying One Move to one Collocation 31
3.3.4 Using the Proposed HMM to Automatically Label TD 31
Chapter 4 Experiments and Evaluation 33
4.1 Experimental Setting 33
4.2 Evaluation 38
4.2.1 Evaluation Metric 38
4.2.2 Analysis of Performance 39
Chapter 5 Discussion 41
5.1 Comparison with Mover 41
5.2 Analysis of Errors 42
5.3 Limitations of the Study Regarding the Lanugae Processing 44
Chapter 6 Application 45
6.1 Online Learning Tool—CARE 45
6.2 Applying CARE in a Classroom Setting 48
6.2.1 Tests 49
6.2.2 Questionnaires 50
6.2.3 Results 50
Chapter 7 Conclusion and Future Work 57
7.1 Overview 57
7.2 Directions for Future Research 57
References 59
Appendix A – The Expermental Results 63
Appendix B – The Analyses of TD with Errors 68
Appendix C – Background Questionnaire 72
Appendix D – An Example of Abstract 74
Appendix E – Tests of Move Analysis 76
Appendix F – The Evaluation Questionnaire (Computer Science) 78
Appendix G – The Evaluation Questionnaire (Electronic Engineering) 79
Appendix H –The Results of Background Questionnaire 80
Appendix I – The Results of Evaluation Questionnaire 84
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