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  • 學位論文

高相關性引用與相關而未被引專利之發掘─以書目耦合與共被引為依據

Manifesting Relevant Patent Citations and Relevant Un-cited Patents Using Bibliographic Coupling and Co-Citation

指導教授 : 陳達仁

摘要


專利引文分析是以專利間引用關係做為分析的基礎,其中包括專利重要性之量測、知識流及知識外溢現象之研究、技術演進之軌跡分析等等。然而,專利之間的引用關係卻存在疑慮,為了引用所有相關資訊,專利會引用和其相關性低之資料,更甚者,高度相關的專利資訊會因為缺乏時間或是競爭關係而沒有被註記為引用資料。本篇論文旨在利用專利間書目耦合 (Bibliographic coupling, BC) 及共被引 (Co-citation, CC) 之關係,區別引用之相關性以找出高相關性引用,以及發掘相關而未被引之專利。本研究提出引用時間延遲(Citation time lag) ,係指一被引專利被另一專利引用之時間差。分析發現高相關性引用之延遲時間一般來說較短,且引用延遲時間越短的高相關性引用其相關性更高,尤以BC所找出的高相關性引用表現此特性更明顯。相關性越高引用延遲時間越短之現象也發生在相關而未引的專利對上,且同樣BC較CC明顯,說明大部分由BC找出來之相關未引之關係是因為缺乏時間。此外,利用高相關性引用及相關而未引關係所建構之網路計算專利之被引次數更能反映專利之重要性。本論文以電動運輸工具技術(electric vehicle technology) 作為衡量研究方法可行性的研究個案。研究結果顯示,不論是用於發掘高相關性引用或相關而未引之關係,書目耦合確實能反映專利間引用之相關性,且比共被引方法有更佳之效果。

並列摘要


Patent citations are extensively used for measuring the importance of patents, regarded as the knowledge flow among countries and technology fields for analysis, and applied to mapping technological trajectories for studying the evolution of the technology. However, patent citation analysis is subject to some uncertainties. Many patents are cited only with slightly relevant because they are only related to one very specific technical aspect. Moreover, many patents which should have been cited are missed. This paper aims to identify the relevant citations and the relevant un-cited patents in order to present the more precise view in the citation relationships. Both of BC and CC methods are utilized to identify the relevant citations and the relevant un-cited patents. Besides, the occurrence of relevant citations and relevant un-cited patents are related to the citation time lag (CTL), which is the time necessary for the cited patent being cited by the citing patent. The results show that citations with shorter CTL are more possible to be relevant, and this phenomenon is more obvious by BC. It reveals that it takes time for any two patents to establish their CC relations. Some relevant information cannot be dug out by CC, and therefore BC is the better approach of the identification.

參考文獻


Albert, M., Avery, D., Narin, F., & McAllister, P. (1991). Direct validation of citation counts as indicators of industrially important patents. Research Policy, 20(3), 251-259.
Bassecoulard, E., Lelu, A., & Zitt, M. (2007). Mapping nanosciences by citation flows: A preliminary analysis. Scientometrics, 70(3), 859-880.
Bichteler, J. and Parsons, R.G. (1974). Document retrieval by means of an automatic classification algorithm for citations. Information Storage and Retrieval, 10(7-8), 267-278.
Breschi, S., & Lissoni, F. (2005). Knowledge network from patent data. Handbook of quantitative science and technology research, 613-643.
Carpenter, M., & Narin, F. (1983). Validation study: Patent citations as indicators of science and foreign dependence. World Patent Information, 5(3), 180-185.

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