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題名 古籍數位人文研究平台之史料人物關係圖工具發展與應用-以明代文集之人物為例
Development and Application of Ancient Books Digital Humanities Research Platform with Characters’ Relationship Map - A Case Study of the Characters in the Ming Dynasty Ancient Books
作者 張鐘
Chang, Chung
貢獻者 陳志銘
Chen, Chin-Ming
張鐘
Chang, Chung
關鍵詞 數位人文
社會網絡分析
人機互動
文本探勘
資訊視覺化
Digital humanities
Social network analysis
Human–computer interaction
Text mining
Data visualization
日期 2018
上傳時間 6-八月-2018 18:11:13 (UTC+8)
摘要 本研究旨在開發支援數位人文研究之「古籍數位人文研究平台之史料人物關係圖」,能自動識別文本中的人名,同時提供易上手的即時互動介面,透過人機互動方式協助人文學者更有效率且正確的建立擬分析文本之人物社會關係,以探索複雜的人物社會網絡關係,找到有用的研究發現。本研究以實驗研究法比較有無使用本研究發展之「史料人物關係圖系統」在支援人文學者解讀文本中的人物與人物關係成效,以及科技接受度是否具有顯著差異,並輔以半結構式深度訪談了解人文學者對於本研究發展之「史料人物關係圖」的看法與感受,也使用滯後序列分析析受測者使用「史料人物關係圖」解讀人物與人物關係的行為歷程,以及解讀人物與人物成效及關係,與受測者使用「史料人物關係圖」系統的行為歷程之間是否具有顯著關聯性。
實驗結果發現,採用本研究發展之史料人物關係圖系統,在解讀人物與人物關係成效上高於使用無史料人物關係圖的系統,但未達顯著差異;採用史料人物關係圖系統的技接受度顯著高於無史料人物關係圖的系統。而相關分析部分,使用「史料人物關係圖」系統解讀文本中的人物成效與解讀文本中的人物關係成效之間達顯著正相關,但與使用者行為歷程之間無顯著關聯性。由訪談結果歸納得知,受訪者對系統介面的整合與操作的流暢度給予正面的評價;史料人物關係圖部分,多數受訪者認為史料人物關係圖能方便他們了解整體文本中的人物脈絡,但人名辨識的準確性仍有待改善。未來將利用機器學習方法,建立明代文集人名的實體命名辨識模型,以及提供社會網絡相關測度,讓系統更加完善,提高輔助人文學者解讀人物與人物關係的效益。
This research aims to develop the Books Digital Humanities Research Platform with Characters’ Relationship Map, which is able to identify the characters from the ancient books automatically. It also provides the user-friendly interface and helps humanities scholars to interpret characters’ relationship more efficiently and accurately by way of Human-Computer Interaction. Humanities scholars can discover the characters’ complex social network through the Characters’ Relationship Map to obtain useful findings.
With experimental method, the research compared the outcomes with and without the Characters’ Relationship Map assisting humanities scholars to interpret the character and the characters’ relationship in the ancient books, and if there were significant differences in technology acceptance. Via semi-structured in-depth interviews, the research acquired humanities scholars’ opinions and perception about the Characters’ Relationship Map. The research utilized lag sequence analysis to analyze users’ behavior processes and achievements of using Characters’ Relationship Map as well as investigating the correlations between users’ behavior processes and achievements.
The experimental results show that the system with the Characters’ Relationship Map is higher than the system without the Characters’ Relationship Map in both the interpretation of the character and the interpretation of the characters’ relationship, but not significant. The technology acceptance analysis reveals that the system with the Characters’ Relationship Map has significantly better technology acceptance than the system without the Characters’ Relationship Map. There is significant correlation between the achievements of interpreting the character and the characters’ relationship, but no significant correlation among users’ behavior processes. According to the interviews, respondents gave positive comments on the integration and operational fluency of the system interface. Many respondents believed that the Characters’ Relationship Map could help them better understand the context of the characters in the overall text, but the accuracy of the identification of names still needs to be improved.
In the future, we will use machine learning to establish name entity model for Ming Dynasty and also provide social network related measures to make the system more perfect so as to raise the benefits of assisting humanities scholars to interpret characters and characters’ relationship.
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描述 碩士
國立政治大學
圖書資訊與檔案學研究所
105155004
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105155004
資料類型 thesis
dc.contributor.advisor 陳志銘zh_TW
dc.contributor.advisor Chen, Chin-Mingen_US
dc.contributor.author (作者) 張鐘zh_TW
dc.contributor.author (作者) Chang, Chungen_US
dc.creator (作者) 張鐘zh_TW
dc.creator (作者) Chang, Chungen_US
dc.date (日期) 2018en_US
dc.date.accessioned 6-八月-2018 18:11:13 (UTC+8)-
dc.date.available 6-八月-2018 18:11:13 (UTC+8)-
dc.date.issued (上傳時間) 6-八月-2018 18:11:13 (UTC+8)-
dc.identifier (其他 識別碼) G0105155004en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/119210-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 圖書資訊與檔案學研究所zh_TW
dc.description (描述) 105155004zh_TW
dc.description.abstract (摘要) 本研究旨在開發支援數位人文研究之「古籍數位人文研究平台之史料人物關係圖」,能自動識別文本中的人名,同時提供易上手的即時互動介面,透過人機互動方式協助人文學者更有效率且正確的建立擬分析文本之人物社會關係,以探索複雜的人物社會網絡關係,找到有用的研究發現。本研究以實驗研究法比較有無使用本研究發展之「史料人物關係圖系統」在支援人文學者解讀文本中的人物與人物關係成效,以及科技接受度是否具有顯著差異,並輔以半結構式深度訪談了解人文學者對於本研究發展之「史料人物關係圖」的看法與感受,也使用滯後序列分析析受測者使用「史料人物關係圖」解讀人物與人物關係的行為歷程,以及解讀人物與人物成效及關係,與受測者使用「史料人物關係圖」系統的行為歷程之間是否具有顯著關聯性。
實驗結果發現,採用本研究發展之史料人物關係圖系統,在解讀人物與人物關係成效上高於使用無史料人物關係圖的系統,但未達顯著差異;採用史料人物關係圖系統的技接受度顯著高於無史料人物關係圖的系統。而相關分析部分,使用「史料人物關係圖」系統解讀文本中的人物成效與解讀文本中的人物關係成效之間達顯著正相關,但與使用者行為歷程之間無顯著關聯性。由訪談結果歸納得知,受訪者對系統介面的整合與操作的流暢度給予正面的評價;史料人物關係圖部分,多數受訪者認為史料人物關係圖能方便他們了解整體文本中的人物脈絡,但人名辨識的準確性仍有待改善。未來將利用機器學習方法,建立明代文集人名的實體命名辨識模型,以及提供社會網絡相關測度,讓系統更加完善,提高輔助人文學者解讀人物與人物關係的效益。
zh_TW
dc.description.abstract (摘要) This research aims to develop the Books Digital Humanities Research Platform with Characters’ Relationship Map, which is able to identify the characters from the ancient books automatically. It also provides the user-friendly interface and helps humanities scholars to interpret characters’ relationship more efficiently and accurately by way of Human-Computer Interaction. Humanities scholars can discover the characters’ complex social network through the Characters’ Relationship Map to obtain useful findings.
With experimental method, the research compared the outcomes with and without the Characters’ Relationship Map assisting humanities scholars to interpret the character and the characters’ relationship in the ancient books, and if there were significant differences in technology acceptance. Via semi-structured in-depth interviews, the research acquired humanities scholars’ opinions and perception about the Characters’ Relationship Map. The research utilized lag sequence analysis to analyze users’ behavior processes and achievements of using Characters’ Relationship Map as well as investigating the correlations between users’ behavior processes and achievements.
The experimental results show that the system with the Characters’ Relationship Map is higher than the system without the Characters’ Relationship Map in both the interpretation of the character and the interpretation of the characters’ relationship, but not significant. The technology acceptance analysis reveals that the system with the Characters’ Relationship Map has significantly better technology acceptance than the system without the Characters’ Relationship Map. There is significant correlation between the achievements of interpreting the character and the characters’ relationship, but no significant correlation among users’ behavior processes. According to the interviews, respondents gave positive comments on the integration and operational fluency of the system interface. Many respondents believed that the Characters’ Relationship Map could help them better understand the context of the characters in the overall text, but the accuracy of the identification of names still needs to be improved.
In the future, we will use machine learning to establish name entity model for Ming Dynasty and also provide social network related measures to make the system more perfect so as to raise the benefits of assisting humanities scholars to interpret characters and characters’ relationship.
en_US
dc.description.tableofcontents 第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究問題 5
第四節 研究範圍與研究限制 6
第五節 名詞解釋 7
第二章 文獻探討 9
第一節 數位人文 9
第二節 社會網絡分析 15
第三節 系統評估理論 19
第三章 系統設計 23
第一節 系統架構 23
第二節 系統元件 27
第三節 系統開發工具 31
第四節 系統介面與功能 33
第四章 研究設計與實施 39
第一節 研究方法 39
第二節 研究對象 40
第三節 研究工具 40
第四節 研究架構 42
第五節 實驗流程 45
第六節 資料分析 49
第七節 研究實施步驟 51
第五章 實驗結果與分析 53
第一節 研究對象基本資料 54
第二節 有無史料人物關係圖系統解讀文本人物關係之成效比較分析 55
第三節 有無史料人物關係圖系統之科技接受度差異比較分析 57
第四節 史料人物關係圖系統使用行為分析 62
第五節 訪談分析 70
第六章 結論與建議 87
第一節 結論 87
第二節 系統改善建議 92
第三節 未來研究方向 94
參考文獻 97
中文部分 97
英文部分 99
附錄一 第一階段文本人物關係評估表 104
附錄二 第二階段文本人物關係評估表 105
附錄三 有史料人物關係圖科技接受度問卷 106
附錄四 無史料人物關係圖科技接受度問卷 107
附錄五 訪談大綱 108
zh_TW
dc.format.extent 2384910 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105155004en_US
dc.subject (關鍵詞) 數位人文zh_TW
dc.subject (關鍵詞) 社會網絡分析zh_TW
dc.subject (關鍵詞) 人機互動zh_TW
dc.subject (關鍵詞) 文本探勘zh_TW
dc.subject (關鍵詞) 資訊視覺化zh_TW
dc.subject (關鍵詞) Digital humanitiesen_US
dc.subject (關鍵詞) Social network analysisen_US
dc.subject (關鍵詞) Human–computer interactionen_US
dc.subject (關鍵詞) Text miningen_US
dc.subject (關鍵詞) Data visualizationen_US
dc.title (題名) 古籍數位人文研究平台之史料人物關係圖工具發展與應用-以明代文集之人物為例zh_TW
dc.title (題名) Development and Application of Ancient Books Digital Humanities Research Platform with Characters’ Relationship Map - A Case Study of the Characters in the Ming Dynasty Ancient Booksen_US
dc.type (資料類型) thesisen_US
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dc.identifier.doi (DOI) 10.6814/THE.NCCU.LIAS.009.2018.A01-