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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/112196

    Title: 支援數位人文研究之文本自動標註系統發展與使用評估研究
    Development and evaluation of an automatic text annotation system for supporting digital humanities research
    Authors: 劉鎮宇
    Liu, Chen Yu
    Contributors: 陳志銘
    Chen, Chih Ming
    Liu, Chen Yu
    Keywords: 數位人文
    Digital humanities
    Automatic annotation system
    Automatic Chinese word segmentation
    Linked data
    Date: 2017
    Issue Date: 2017-08-28 11:37:33 (UTC+8)
    Abstract: 在傳統的人文研究中,人文學者大多以如古籍珍善本、歷史文獻等紙本出版形式之文本為主要研究文本型式,但是隨著資訊社會的來臨,許多研究機構陸續將這些紙本資料進行數位化並建置數位典藏資料庫,對人文研究環境與知識取得管道帶來巨大的改變,基於數位閱讀之文本研究型式也成為必然的發展趨勢。
    因此,本研究發展支援數位人文研究之「文本自動標註系統」,藉由Linked Data的概念匯集來自不同資料庫的資源,並加以整合後,替文本進行自動註解,讓使用者在解讀文本時能夠即時參照其他資料庫的資源,並提供友善的具文本標註之閱讀介面,以利於人文學者透過閱讀進行資料的解讀。本研究以實驗研究法比較本研究所發展之「文本自動標註系統」與「MARKUS文本半自動標註系統」在支援人文學者進行文本資料解讀之閱讀成效與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「文本自動標註系統」的看法及感受,也進一步分析「文本自動標註系統」閱讀成效、科技接受度及使用者行為歷程之間是否具有關聯性。
    In traditional humanities research, most humanities scholars studied text-type paper-based publishing texts, such as rare ancient books and historical literature. However, many research institutes, in the information society, gradually digitalized such paper-based data and established digital archives database to result in great changes in humanities research environment and knowledge acquisition channels. The research pattern with digital reading based texts became the essential development trend.
    For this reason, an “automatic text annotation system” for supporting digital humanities research is developed in this study. Resources from distinct database are gathered through Linked Data and integrated for the automatic annotation of texts. It allows users immediately referring to resources from other database when interpreting texts and provides friendly reading interface with text annotation for humanities scholars interpreting data through reading. With experimental research, the “automatic text annotation system” developed in this study is compared with “MARKUS semi-automatic text annotation system” for supporting humanities scholars interpreting text data to discussed the difference in reading achievement and technology acceptance. Semi-structured in-depth interviews are also proceeded to understand humanities scholars’ opinions and perception about the “automatic text annotation system” developed in this study as well as to analyze the correlations among reading achievement, technology acceptance, and user behavior course of the “automatic text annotation system”.
    The experimental findings show that the reading achievement with the automatic text annotation system developed in this study is higher than that with MARKUS semi-automatic text annotation system, but not achieving the significance. The technology acceptance analysis reveals remarkably better technology acceptance of the automatic text annotation system than MARKUS semi-automatic text annotation system. According to the interviews, the reading interface of the automatic text annotation system is simple and clear that it is more suitable for reading than MARKUS semi-automatic text annotation system. The ease of use and usefulness of reading interface is a key factor in humanities scholars accepting the system for the digital humanities research. In regard to the comparison of similar functions between two systems, the functions of vocabulary enquiry, linking to source web sites, and annotation appending of the automatic text annotation system are more intuitive and easy to use than those of MARKUS semi-automatic text annotation system. What is more, humanities scholars emphasize more on the sentence segmentation function than the automatic word segmentation function, and the linked source database, Moedict, appears the best assistance. Finally, there is no significant correlation between reading achievement and user behavior course with the automatic text annotation system.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104155014
    Data Type: thesis
    Appears in Collections:[圖書資訊與檔案學研究所] 學位論文

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