應用書目計量方法與文字採礦分析輔助科技的研究發展;Bibliometric analysis with text mining in assistive technology

NCUIR > School of Management at National Central University > Executive Master of Business Administration > Electronic Thesis & Dissertation > Item 987654321/80546

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Title:	應用書目計量方法與文字採礦分析輔助科技的研究發展;Bibliometric analysis with text mining in assistive technology
Authors:	葉佐軒;Yeh, Tso-Hsuan
Contributors:	企業管理學系在職專班
Keywords:	輔助科技;書目資料分析;文字探勘;文字採礦;Assistive technology;Bibliometric analysis;Text Mining;Network Analysis
Date:	2019-07-23
Issue Date:	2019-09-03 14:44:21 (UTC+8)
Publisher:	國立中央大學
Abstract:	輔助科技被定義為任一可用的裝置或系統，可以輔助並促進單一個人完成原本能力所無法完成的事項，並可提升使用時的安全性和降低完成任務的困難度。在本研究中，藉由資料圖形化和文字採礦(Text mining)的方式，分析大量與輔助科技相關文獻的書目資料文本，從綜觀的角度找出輔助科技的發展趨勢。研究中，使用Scopus作為主要資料來源的資料庫，並以2000年到2018年的文本資料作為主要分析區間。從分析結果中根據每年出版的相關文獻，顯示和輔助科技有關聯的議題討論從2006年開始便有顯著的提升，整體而言是呈現逐年增加的趨勢。在區域分佈上，作者來源和貢獻度以美國和英國最多。Accessibility出現在作者關鍵字中的高頻率，顯示輔助科技的發展和推廣還存在著很多限制和障礙，且大多都在於導入成本或是使用者對於社會觀感的在意程度。而在書目耦合(bibliography coupling)分析中，神經科學(neural science)是連結強度最高的議題。文字採礦(text mining)分析結果顯示，technology、rehabilitation、disability、education是2000年到2018年的區間中和輔助科技同時出現次數最高的單詞，另外，在2018年首次出現的單詞為innovation和collaboration。本研究從大量書目資料中抽取出現頻率最高的關鍵字、出版貢獻度最高的國家、以及作者和文獻之間的連結關係，以期能提供輔助科技在未來發展方向的一個參考。;Assistive technology (AT) is an umbrella term for any device or system that allows individuals to perform tasks they would otherwise be unable to do or increase the ease and safety with which the tasks can be performed. The objective of this thesis is to conduct data visualization and text mining on bibliography information to provide a comprehensive overview of assistive technology development. Results from this study indicate that the AT-related publications have kept increasing, especially since 2006. From the perspective of research articles, the U.S. and the U.K. are the most productive countries. Term “accessibility” is the most frequent author keyword among the AT-related research, which shows that the cost of devices and the public perception towards AT still limit the use of AT devices. From the result of bibliographic coupling analysis, “neural science” is the most discussed term co-cited by authors because it has the strongest coupling strength. Meanwhile, the text mining results indicate that terms such as “innovation” and “collaboration” first appear in 2018. In short, this study extracts the strongest keywords, the most productive authors and countries, and the network relationships between authors and literatures among the research publications, which can provide development trend and research direction for the communities who are interested in AT research.
Appears in Collections:	[Executive Master of Business Administration] Electronic Thesis & Dissertation

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