博碩士論文 etd-0627118-101540 詳細資訊


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姓名 黃偉恩(Wei-En Huang) 電子郵件信箱 cksh11233@gmail.com
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 106學年第2學期
論文名稱(中) 利用網路搜尋量作為市場需求面以衡量專利價值
論文名稱(英) Using web search data as market demand to assess patent value
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    紙本論文:5 年後公開 (2023-07-27 公開)

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    摘要(中) 在專利分析的中衡量專利的價值是一件重要而且困難的任務。過去的研究需要仰賴專家來 評估專利價值,但是這非常耗費人力與時間。因此近期的研究都利用代理變數來表示專利 價值,例如:專利是否有被核駁、專利的拍賣價格和專利的壽命等。而本研究想站在需求 的角度來衡量專利的價值。我們認為大眾對知識與技術的關注反映了這項知識與技術的重 要性以及其價值,而我們稱大眾的關注程度為社群聲量。我們利用了搜尋資料分析方法來 計算社群聲量。搜尋資料的來源為 Google Trend。我們萃取了專利中的名詞片語作為當篇 專利的核心知識與技術,並且利用詞向量模型來整合同義詞。接者我們利用專利中的名詞 片語作為關鍵字來取得搜尋量,並經過進一步的計算來取得兩種類型的社群聲量,總量類 型社群聲量以及趨勢類型社群聲量。我們討論了兩種不同的案例,科技導向案例以及公司 導向案例。在這些案例中我們觀察社群聲量與專利信息之間的關係,並且將結果和過去的 研究做比較。研究結果顯示,總量類型社群聲量和專利信息的關係和過去的研究有相似的 結果,而趨勢類型社群聲量和專利信息的關係有著相反的結果。總結來說,我們是能夠利 用總量類型社群聲量來衡量專利價值的,而趨勢類型社群聲量提出了一個全然不同的觀點 來衡量專利價值。
    摘要(英) Assessing the value of patents is an important and difficult task in patent analysis. Some prior studies relied on experts to assess the value of patents, but it is time and labor consuming. As a result, recent studies tried to use some proxy variable to represent the patent value such as the binary occurrence of an opposition for the patent, the patent auction price, and the patent lifetime. In this study, we want to stand on the demand side to estimate the patent value. We believe that the attention to the knowledge and techniques of people can reflect the importance and the value of these knowledge and techniques and we call the degree of the attention as social voice. We apply search data analysis to calculate the social voice. The search data is from Google Trend. We extract the noun phrases of patents as the key knowledge and techniques and train a word2vector model to aggregate the similar semantic words. Then, we used these noun phrases as keywords to fetch the search volume and do further calculation and finally we get the two types of social voice, the total type and the trend type. We discuss two types of datasets, the technology-based dataset and the company-based dataset. In these datasets, we observe the relationship between our social voice and the patent information and compare our results with the prior studies. The results show that the relationship between total type social voice and patent information is similar to the prior studies and the relationship between trend type social voice and patent information is opposite to the prior studies. In conclusion, it is possible to use the total type social voice to assess the value of patent and the trend type social voice presents a whole new perspective to discuss the value of patent.
    關鍵字(中)
  • 專利信息
  • 詞向量模型
  • 專利價值
  • 搜尋資料分析方法
  • 專利分析
  • 關鍵字(英)
  • patent information
  • word2vector
  • patent analysis
  • patent value
  • search data analysis
  • 論文目次 [審定書+i]
    [ACKNOWLEDGEMENT+ii]
    [摘要+iii]
    [ABSTRACT+iv]
    [TABLE OF CONTENTS+v]
    [LIST OF FIGURES+vi]
    [LIST OF TABLES+vii]
    [INTRODUCTION+1]
    [RESEARCH IDEA & RESEARCH QUESTION+4]
    [LITERATURE REVIEW+5]
    [SOCIAL VOICE AND WEB SEARCH DATA+5]
    [PATENT VALUE+6]
    [FACTORS USED TO DETERMINE PATENT VALUE+6]
    [METHODOLOGY+8]
    [DATA COLLECTION+9]
    [NOUN PHRASE EXTRACTION & SYNONYM DETECTION+16]
    [SOCIAL VOICE CALCULATION+18]
    [FACTOR EXTRACTION+19]
    [EMPIRICAL ANALYSIS RESULT+23]
    [VIRTUAL REALITY DATASET+23]
    [SELF-DRIVING CAR DATASET+24]
    [GOOGLE DATASET+25]
    [SOCIAL VOICE AND FINANCIAL MARKET+27]
    [FURTHER ANALYSIS: RENEWAL PREDICTION+29]
    [FURTHER ANALYSIS: SOCIAL VOICE WITH KNOWLEDGE FLOW+31]
    [CONCLUSION+31]
    REFERENCES+34]
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    口試委員
  • 林耕霈 - 召集委員
  • 宋皇志 - 委員
  • 林怡伶 - 指導教授
  • 口試日期 2018-07-20 繳交日期 2018-07-27

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