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【目的】归纳基于文本专利技术挖掘通用流程,提炼其中关键技术,并对典型挖掘场景进行分析。【文献范围】以“专利挖掘、专利分析”等关键词在Elsevier、Springer、CNKI数据库进行检索,并参考全球技术挖掘相关会议,共阅读相关文献105篇,实际参考文献66篇。【方法】梳理其关键技术专利知识表示的研究现状与发展趋势,选取三类典型技术挖掘场景进行分析,通过归纳总结、提炼出专利技术挖掘未来发展趋势与研究热点。【结果】专利知识表示的粒度与结构决定了专利技术挖掘的深度、广度与维度。基于SAO基础语义单元,面向技术难题与解决方案的专利技术挖掘有望成为未来发展趋势与研究热点。【局限】本研究仅探讨现有文本挖掘、统计分析、自然语言处理技术在专利技术挖掘中的应用情况,对这些技术本身的发展趋势关注不足。【结论】本研究有助于全面了解专利技术挖掘的概貌、涉及的关键技术及主要应用场景。
【Objective】 The paper summarizes the general process based on the patent technology of patent, extracts the key technologies and analyzes the typical mining scenarios. 【Scope】 The article searches the Elsevier, Springer and CNKI databases with keywords such as “patent mining and patent analysis”, and refers to the related conferences of global technology mining for a total of 105 related literatures and 66 actual references. 【Method】 Combining the research status and development trend of patent knowledge representation of its key technologies, three types of typical technology mining scenarios were selected for analysis. Through summarizing and summarizing, patented technologies were extracted to explore the future development trends and research hot spots. 【Result】 The granularity and structure of patent knowledge determines the depth, breadth and dimension of patent technology mining. Based on the basic semantic unit of SAO, the exploitation of patented technology oriented to technical problems and solutions is expected to become a hot topic in the future. [Limitations] This study only discusses the application of existing text mining, statistical analysis and natural language processing techniques in patent technology mining, and pays insufficient attention to the development trend of these technologies. 【Conclusion】 This study helps to fully understand the overview of patent technology mining, the key technologies involved and the main application scenarios.