| Summary: | 碩士 === 國立暨南國際大學 === 資訊管理學系 === 96 === In recent years, there are many applications for patent analysis to forecast emerging technologies. Especially, citation plays an important role in the patent analysis field. However, current patent citations have certain drawbacks, such as that is difficult to grasp the overall relationship among patent documents, and citation analysis is a time-consuming task because it requires an exhaustive search. Therefore, this thesis applies an incidence matrix to analyze the citation information in patent citation networks. In order to analyze the patent citation and identify the critical patents more effectively, the matrix is analyzed using two algorithms, the topological sorting algorithm and the triangularization algorithm are combined with network measurements as a result of those contributions. Finally, some general discussions of patterns from the results of a patent citation model are presented along with conclusions.
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