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研究生:沈嘉誠
研究生(外文):SHEN, JIA-CHENG
論文名稱:基於LDA之社交型機器人主題演化分析
論文名稱(外文):Topic Evolution Analysis for Social Robots Based on Latent Dirichlet Allocation
指導教授:董惟鳳董惟鳳引用關係
指導教授(外文):Tung, Wei-Feng
口試委員:董惟鳳呂奇傑盧浩鈞
口試委員(外文):Tung, Wei-FengLu, Chi-JieLu, Hao-Chun
口試日期:2021-04-29
學位類別:碩士
校院名稱:輔仁大學
系所名稱:資訊管理學系碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2021
畢業學年度:109
語文別:中文
論文頁數:98
中文關鍵詞:主題模型主題演化社交型機器人隱含狄利克雷分佈
外文關鍵詞:Topic ModelTopic EvolutionSocial RobotsLatent Dirichlet Allocation
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隨著機器人的市場快速發展,社交型機器人受到全球越來越多的關注,以致該領域的研究數量亦日益上升。為了解社交型機器人相關領域的研究發展與面臨的問題,分析社交型機器人的發展歷程與追蹤研究趨勢是至關重要的。透過該的領域主題研究可以從中分析領域主題的發展歷程與發展趨勢,藉此可幫助企業與學者在創新技術的研發與相關應用獲得幫助。

因此本研究從Web of Science期刊資料庫,選取2006年至2020年關於社交型機器人的文獻摘要共計1406篇,並作為研究資料主體。以主題強度演化與主題內容演化兩個維度來分析社交型機器人近年來的科研主題演化趨勢。研究結果如下:(一)早期階段,系統技術的研究佔比較高,後因系統技術的逐步完善帶動了多元化的研究,從而導致系統技術的研究佔比下降而其他領域研究佔比上升(例如高齡者陪伴與健康護理、以及商業應用)。(二)社交型機器人的發展主要以系統技術、關於兒童的相關研究與關於高齡者的相關研究作为三條主線路發展,而醫療、陪伴、教育、互動、商業應用等子主題會各自圍繞發展主軸並獨立發展,形成多元化的研究。

As a consequence of the robot market with rapid development. social robots also attract extensive attention worldwide. In order to understand the opportunities of development , it would be significantly important to understand the existing researches and developments as well as problems and challenges. Therefore, it is to track the process of developments and trend variations. In this study, analyzing the literature related to social robots from academic journals databases, which could contribute the analyzed results to the both of enterprises and academic scholars for their product’s R&D of innovative social robots’ and research topics in the next few years.

In this research, there are 1406 abstracts of research literature about social robots from 2006 to 2020 selected from Web of Science (WOS) database as the main document data. Furthermore, the evolution trends and contents of the research about social robots in recent years derived from two dimensions which are topic intensity evolution and topic content evolution. This research results are as follows: (1) At the early stage, the research on system technology accounted for a relatively high proportion, and then with the increasing development of the system technology which promote the diversification of the researches, while (2) the development of social robots is mainly focused on three branches which include system technology, children, and elderly people. However, the subtopics will be developed independently around the main topic of developments, for instance, medical care, accompanying care, education, interaction and business application, and then it formed the more diversified studies.

表 次 VII
圖 次 IX
第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第貳章 文獻探討 5
第一節 社交型機器人的相關研究 5
第二節 主題模型(TOPIC MODEL) 8
第三節 主題演化(TOPIC EVOLUTION) 16
第參章 研究方法 21
第一節 研究架構 21
第二節 資料蒐集 24
第三節 資料預處理 26
第四節 LDA主題建模 30
第五節 主題強度(TOPIC INTENSITY) 34
第六節 主題相似度(TOPIC SIMILARITY) 36
第七節 主題詞彙探測 39
第肆章 研究分析結果 41
第一節 主題強度演化分析 41
第二節 主題內容演化分析 50
第伍章 結論與建議 61
第一節 研究結果與貢獻 61
第二節 研究限制與未來研究 63
參考文獻 65
附錄一、主題內容演化之主題相似度數據 73
附錄二、主題內容演化之各主題-詞機率分佈數據 76
附錄三、主題詞彙探測數據 82
附錄四、停用詞庫 86


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