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題名：建構半導體代工業專利分類支援系統：專利共同引用分析的觀點
作者：吳曉君 引用關係
作者(外文)：Shiao-Jun Wu
校院名稱：國立雲林科技大學
系所名稱：管理研究所博士班
指導教授：賴奎魁
學位類別：博士
出版日期：2003
主題關鍵詞：分類；專利分析；共同引用；patent analysis；co-citation；classification
原始連結：連回原系統網址new window
相關次數：
  • 被引用次數被引用次數:期刊(6) 博士論文(1) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:6
  • 共同引用共同引用:0
  • 點閱點閱:45
IPC或UPC是各國專利局使用的專利分類系統。由於IPC或UPC是產業通用的分類系統，以分類結果進行產業專利分析時，分析結果無法有效的為企業進行研發規劃、技術定位、專利策略的制定等管理工作。因此，配合產業技術特性，發展產業專用的專利分類系統是專利管理的基本課題。本研究提出的專利共同引証分析(Patent Co-Citation Approach, PCA)是使用書目計量學文獻分析的技巧，以定義專利分類系統的方法論。分析過程分三階段進行：第一階段，依研究對象及研究目的選擇合適的專利資料庫以檢索專利，並篩選基礎專利。第二階段，以基礎專利對共同被引証的次數衡量基礎專利的相似性。第三階段，採用因素分析定義分類系統並評估分類系統的分類績效。
對半導體代工業進行PCA的實証分析，並比較IPC、UPC、PCA三種分類系統的差異。研究結果發現，PCA提供的技術資訊較另外二個分類系統豐富，對於專利分析、專利資訊管理、專利分析、專利佈署四個專利管理的階段，亦提供了具體的協助。
The paper proposes a new approach to create a patent classification system to replace the IPC or UPC system for conducting patent analysis and management. The new approach is based on co-citation analysis of bibliometrics. The traditional approach for management of patents, which is based on either the IPC or UPC, is too general to meet the needs of specific industries. In addition, some patents are placed in incorrect categories, making it difficult for enterprises to carry out R&D planning, technology positioning, patent strategy-making and technology forecasting. Therefore, it is essential to develop a patent classification system that is adaptive to the characteristics of a specific industry. The analysis of this approach is divided into 3 phases. Phase I selects appropriate databases to conduct patent searches according to the subject and objective of this study and then select basic patents. Phase II uses the co-cited frequency of the basic patent pairs to assess their similarity. Phase III uses factor analysis to establish a classification system and assess the efficiency of the proposed approach. The main contribution of this approach is to develop a patent classification system based on patent similarities to assist patent manager in understanding the basic patents for a specific industry, the relationships among categories of technologies and the evolution of a technology category. PCA can provide rich information for patent analysis than other classification systems.
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