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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林峰田 | |
| dc.contributor.author | Lan-Ting Tseng | en |
| dc.contributor.author | 曾蘭婷 | zh_TW |
| dc.date.accessioned | 2021-06-12T17:53:35Z | - |
| dc.date.available | 2008-03-25 | |
| dc.date.copyright | 2008-03-25 | |
| dc.date.issued | 2007 | |
| dc.date.submitted | 2008-03-07 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/26998 | - |
| dc.description.abstract | 在2003年，台灣社會受到SARS傳染病的嚴重衝擊。從SARS的事件中，可以觀察到在政令下達的過程中沒有人能忽略跨領域合作的重要性。然而，合作需要溝通。特別是當一個團隊擁有不同的專業者；在許多跨領域的問題情境中，他們必須重視對於某些事物的共同理解。這就是為什麼本研究要針對這個事件且以「社區」一詞為例，提出一個半自動化的方法去把隱含在脈絡當中的概念結構視覺化。
為了分析「社區」一詞，這個研究以運算語言學與建構本體知識工程為基礎提出一個分析性的機制。所謂知識本體的概念結構不外乎區辨概念以及概念與概念之間的關聯性。因此，在不同知識領域(即不同類型的說話者)之間要區辨概念的方法程序，本研究提出的步驟規劃如下： 1.蒐集資料: 在SARS期間的新聞報導與相關文章收集起來，檢索出所有包含「社區」一詞的語句作為基本的分析單元。 2.進行分析: 這個機制為了增加其資料分析的可操作性用來帶動語句型式的轉換。然後，把一個語句分解成tuple來掌握概念與概念之間之運作關係。 3.描繪概念輪廓: 本研究建構了一個基模用來描繪每個語句的概念輪廓。這個基模是一個架構不只可以把一連串語彙的概念予以結構化，而且盡可能地把語境脈絡內隱的詮釋給外顯化。 4.繪製概念圖: 本研究根據分析最後會產生一個形式良好的資料表單來體現其既有文本中的語境脈絡。研究的結果會就語詞外延的意義歸納分類。而且，本研究運用了「GRAPHVIZ」的圖形工具語言描繪其星狀拓樸圖。 本研究的結果是以這些星狀拓樸圖來觀察不同領域之間對於「社區」一詞的不同領域知識本體的轉移現象。為了使研究的方法與結果具有可信度，本研究採取了兩個策略；針對分析結果，本研究透過雙盲測試來檢核並保留可以採信的部分。針對分析方法的合理性，本研究透過全球語料規模最大的「中文詞彙特性速描系統」(CSE)所查詢針對「社區」一詞所搭配的詞組作為基準線來進行對照。還有就是應用一些統計數據的指標來觀測其變異性的程度。然後，運用質性變異指標(IQV)與卡方檢定來評估在變異性的向度上不同領域之間的表現。 | zh_TW |
| dc.description.abstract | In 2003, Taiwan came under the attack of Severe Acute Respiratory Syndrome (SARS). The SARS epidemic had a huge impact on Taiwan society. From the event, we observed that no one can be regardless of interdisciplinary collaboration in the delivering of public policies. However, collaboration needs communication. Especially when a team comprises various professionals; they have to value joint comprehension under trans-disciplinary situations. That is the reason for the research to propose a new semi-automatic skill to visualize implicated contexts in case of the term 「社區[shèqū]」(“community”).
To analyze “community”, this research proposes an analytical mechanism based on computational linguistics and ontological engineering. Hence, the way to identify concepts among knowledge domains (various types of speakers) is a step-by-step procedure: 1.Collecting Data: after retrieving all documents, we keep all the sentences containing the term “community”. A sentence is an entry to be analyzed. 2.Implementing analysis: for data processing, the mechanism is made for carrying transformations to increase the maneuverability. Then, a sentence would be decomposed as tuples to reveal their concepts and operators. 3.Profiling Concepts: the corpus is analyzed to identify concepts and their relationships. Thus, the research creates a schema for profiling each sentence. The schema is a framework not only to structure our knowledge in lexical chains, but also to explicate their interpretations in context. 4.Mapping conceptual graphs: the study generates a well-formed database to exhibit the given texts (community) within their contexts according to the analysis. Results are categorized as the extended senses. Furthermore, the research applies the graphic tool GRAPHVIZ which conveys the star topologies. Conclusively, all the star topologies show various kinds of conceptual structures of “community”. Apparently, there seems to be the shifting of domain ontologies while contrasting to knowledge domains and relationships. To be convinced, we apply two strategies to evaluate the results and the method of the research. For the result, the research uses double-blind test to check the transformation from sentence to tuple. For the method, the research makes a contrast to the Chinese Sketch Engine (CSE) which owns the largest readership globally. Also, we apply several statistic indexes to measure the difference between CSE and the four domains. Then, by ways of Index of Qualitative Variance (IQV) and Chi-square test, the research has verified its method on the dimension of variance and diversity. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-12T17:53:35Z (GMT). No. of bitstreams: 1 ntu-96-D87544005-1.pdf: 23487762 bytes, checksum: ee87d183c5c188d819ecad8fb62d15a4 (MD5) Previous issue date: 2007 | en |
| dc.description.tableofcontents | Table of Contents
Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research Intention 3 1.2.1 Knowledge Engineering 3 1.2.2 Research Objective 4 1.2.3 Research Scope 4 1.3 The Strategy of Research 6 1.4 The Structure of this Dissertation 9 Chapter 2 Literature Review 10 2.1 The Phrasing of “Community” in Urban Studies 10 2.2 Linguistic-computation Approach 13 2.3 The Meaning of “Commnity” in Broad Spectrum 15 2.4 Studies on Ontology 19 2.4.1 Knowledge Engineering 20 2.4.2 Definitions of Ontology 21 2.4.3 Ontological Tasks 23 2.4.4 Conceptualization 26 2.5 Related Works for the Proessing of Linguistic Data 27 2.5.1 Method-driven Approach 28 Component Analysis 28 Formal Conceptual Analysis 29 Relational Concept Analysis 30 Data Mining and Text Mining 31 2.5.2 Problem-driven Approach 33 Qualia Analysis 33 Ontological Semantics 35 Template-matching Analysis 37 Chapter 3 Theoretical Framework 39 3.1 Concepts as Semantic Units 39 3.2 The Key Terminology 44 3.3 The Algorithm for Identifying Concepts 46 3.4 The Strategy for Evaluation 51 Chapter 4 Implementation 53 4.1 The Procedure of Transformation 53 4.2 The Transforming Texts to Corpora 58 4.3 Transforming Corpora to Sentences in a Formal Form 61 4.4 Validation of Entailment 62 Chapter 5 Result Analysis 65 5.1 The Categorization for All Extended Concepts 65 5.2 The Sorting and Ranking of Denoting Concepts 69 5.2.1 “Community”(社區[shèqū]) as a Subject 69 1. the Hypernyms of “Community” 69 2. the Meronyms of “Community” 70 3. the Causes of “Community” 73 4. the Associated Concepts of “Community” 74 5.2.2 “Community” (社區[shèqū]) as an Object 76 1. the Hyponyms of “Community” 76 2. the Holonyms of “Community” 76 3. the Effects of “Community” 77 4. the Correlating Concepts of “Community” 78 5.2.3 The Ranking of Extending Concepts 80 5.3 Some Observations and Considerations on the Results 82 Chapter 6 The Making of Star Topologies 85 6.1 The Legend of Conceptual Graphs 85 6.2 The Star Topologies for the Speakers 90 6.3 The Contrast between Relationships 96 6.3.1 Generalization 96 Government Office 97 Press 98 Medical Doctors 99 Others 100 6.3.2 Aggregation 100 Government Office 101 Press 102 Medical Doctors 103 Others 104 6.3.3 Dependency 105 Press 105 Medical Doctors 107 6.3.4 Association 109 Government Office 109 Press 110 Medical Doctors 111 Others 113 6.4 Summary 114 Chapter 7 Evaluation 116 7.1 The Basic Facts about CSE 116 7.2 The Queries on 「社區[shèqū]」(“Community”) 117 7.3 The Contrasting to CSE 121 7.3.1 about the Frequency 121 7.3.2 about the Tendency 125 7.4 The Observation of Domain Shifting 127 7.4.1 The Measuring of IQV 127 7.4.2 The Chi-Square Testing 129 Chapter 8 Conclusive Discussions 133 8.1 Conclusions 133 8.2 Future Works 137 Appendixes A-F 138 A.The Database of Corpora 139 B.A Schema of Entailment and Formalization 150 C.The Validation of Simple Sentence and Tuples 160 D.Categorization by Speakers 180 E.Classifying the Tuples by Relationships 189 F.the Source Files of Mapping Graphs 200 G.the Source Files of Star Topologies 209 H.the Terms of Various Domain Ontology 223 References 229 | |
| dc.language.iso | en | |
| dc.subject | 本體知識工程 | zh_TW |
| dc.subject | 概念 | zh_TW |
| dc.subject | 運算語言學 | zh_TW |
| dc.subject | SARS | zh_TW |
| dc.subject | 社區 | zh_TW |
| dc.subject | 星狀拓樸 | zh_TW |
| dc.subject | SARS | en |
| dc.subject | star topology | en |
| dc.subject | ontological engineering | en |
| dc.subject | computational linguistics | en |
| dc.subject | community | en |
| dc.subject | concepts | en |
| dc.title | 拓樸語言學取向的概念分析:以社區一詞為例 | zh_TW |
| dc.title | A Topologically Linguistic Approach dor Conceptual Analysis:
A Case Study on 'Community' | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 施宣光,孫志鴻,陳亮全,黃居仁,簡聖芬 | |
| dc.subject.keyword | SARS,社區,運算語言學,本體知識工程,概念,星狀拓樸, | zh_TW |
| dc.subject.keyword | SARS,community,computational linguistics,ontological engineering,concepts,star topology, | en |
| dc.relation.page | 257 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2008-03-07 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 建築與城鄉研究所 | zh_TW |
| 顯示於系所單位： | 建築與城鄉研究所 | |
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