請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 謝舒凱(Shu-Kai Hsieh) | |
| dc.contributor.author | Yongfu Liao | en |
| dc.contributor.author | 廖永賦 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:02:11Z | - |
| dc.date.available | 2022-02-16 | |
| dc.date.available | 2022-11-23T09:02:11Z | - |
| dc.date.copyright | 2022-02-16 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-08 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79507 | - |
| dc.description.abstract | 中文書寫系統在世界書寫系統中具有獨特的地位，因為絕大多數的漢字為語素文字 (logogram)。因此，漢字本身即攜帶語義訊息，而不像許多其他書寫系統需透過拼音對應至詞彙來攜帶語意訊息。此外，漢字通常可以被分解成更小的元素，這些元素常攜帶著與該漢字相關的語意和發音。然而，由於漢字的編碼方式 (encoding)，電腦使用者不容易取得這些豐富的資訊——一個漢字對應到電腦中的一個編碼 (code point)，這讓使用者無法進一步取得漢字的內部結構訊息，因為編碼本身並不會記錄這些資訊。例如，中文使用者會知道，「淋」和「霖」這兩個字的發音相同，因為它們有共同的部件「林」。但是我們無法從「淋」和「霖」的編碼中取得這個共同的部件——在 Unicode 中，「淋」與「霖」分別對應到 U+6DCB 與 U+9716，但這些編碼並無法表徵這兩個字具有關聯的事實。面對這個局限，我們開發了一個可分析子字詞層次的中文語料庫工具。這個語料庫工具讓使用者能夠取得漢字豐富的部件資訊 (包含部首與非部首)，例如，這讓使用者可以根據漢字共有的部件進行檢索 (舉例來說，透過共同部件「林」，可以取得「淋」、「霖」、「琳」、「箖」與「惏」)，並且讓使用者能夠透過這類訊息來進行語料的量化分析。除了語料庫工具之外，我們還進行了一項個案研究，以透過實徵資料驗證子字詞層次的資訊是否有用，並同時探索此階層與更高階層的語意關聯。結果顯示，某些特定的漢字部首語義訊息與詞彙的語義訊息具有顯著的關聯，然而多數的部首與詞彙類型並無明確的對映關係。論文最後，我們指出了漢字內部的高度遞迴結構對於當前研究的一些影響，並討論了解決相關困境的潛在可能。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:02:11Z (GMT). No. of bitstreams: 1 U0001-0802202212352300.pdf: 1717279 bytes, checksum: 272f558132c4fd79dd90b10d0c38460b (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 摘要 v Abstract vii List of Figures xi List of Tables xiii 1 Introduction 1 1.1 Background and Motivation 1 1.2 Contributions 3 1.3 Organization of the Thesis 4 2 Literature Review 7 2.1 Typology of Writing Systems 7 2.2 Chinese Character Structure 13 2.3 Resources for Chinese Character Decomposition 17 2.4 Previous Work on Chinese Character Decomposition 22 3 Design of System 25 3.1 Corpus Structure and Input Data 25 3.2 Corpus Query Language 27 3.3 Searching the Corpus 28 3.4 Corpus Analysis 35 4 Case Study: Radical Semantic Information in Words 49 4.1 Data 50 4.2 Association of Radical and Word Semantic Types 51 4.3 Radical Semantic Type Importance 58 4.4 Interim Summary 65 5 Conclusion 69 5.1 Summary 69 5.2 Limitations and Future Work 70 References 75 Appendix A — Search API in hgct 79 Appendix B — Corpus Analysis API in hgct 87 | |
| dc.language.iso | en | |
| dc.title | 文字部件為本的語料分析：一個子字詞層次的中文語料庫工具 | zh_TW |
| dc.title | Glyph-based Corpus Analysis: A Toolkit for Sub-character Analysis of Chinese Corpora | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳正賢(Ouh-Young Ming),張瑜芸(Lung-Pan Chen),(Yi-Ping Hung) | |
| dc.subject.keyword | 語料庫工具,書寫系統,漢字,部件,語料庫語言學, | zh_TW |
| dc.subject.keyword | corpus toolkit,writing system,Chinese character,character components,corpus linguistics, | en |
| dc.relation.page | 97 | |
| dc.identifier.doi | 10.6342/NTU202200369 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2022-02-10 | |
| dc.contributor.author-college | 文學院 | zh_TW |
| dc.contributor.author-dept | 語言學研究所 | zh_TW |
| 顯示於系所單位： | 語言學研究所 | |
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| U0001-0802202212352300.pdf | 1.68 MB | Adobe PDF | 檢視/開啟 |
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