识别技术演进的专利网络分析——以中国人工智能技术为例

Lu Huang, Wen Miao, Yi Zhang, H. Yu, Kangrui Wang
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引用次数: 7

摘要

识别技术演进是协助技术管理的重要途径。由于现代技术越来越复杂和动态,一般的统计技术很难捕捉到技术演进过程中技术互联的底层信息。然而,复杂网络分析可以被认为是研究这一问题的有力工具。同时,专利文献中包含了丰富的技术演化信息,可以作为重要的数据来源。本文以专利文献中的核心术语为基础,构建技术网络,呈现技术的分布。在连续时间段内网络之间的比较不仅可以提供一种详细了解技术演变的方法,而且可以预测技术机会,这可以用来帮助快速了解选定技术的发展,并为研究和开发(R&D)计划和技术商业化提供见解。以中国人工智能技术演进为例,论证了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patent Network Analysis for Identifying Technological Evolution: A Case Study of China's Artificial Intelligence Technologies
Identifying technological evolution is a crucial way to assist in technology management. Since modern technology has become more and more complex and dynamic, general statistical techniques can hardly capture the underlying information of technological interconnection in the process of technology evolution. However, complex network analysis can be considered to be a powerful tool to investigate this issue. At the same time, patent documents containing rich information to indicate technological evolution in sequential time period can be a significant data source. This paper, based on the core terms derived from patent documents, constructs technological networks, to present the distribution of technologies. The comparison between the networks in sequential time periods can not only provide a way to understand technological evolution in detail, but also forecast technology opportunities, which can be used to help understand the development of selected technologies quickly and provide insights to research and development (R&D) plan and technological commercialization. A case study on exploring the evolution of China's artificial intelligence technologies is conducted to demonstrate the feasibility of this method.
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