利用局部离群因子算法探测核心技术发展趋势——以中国风能专利数据为例

Detecting Core Technology's Development Trend with LOF——Based on Wind Energy Patent Data of China

[目的/意义]为验证局部离群因子算法在探测核心技术及核心技术发展趋势的有效性,丰富专利分析领域的研究。[方法/过程]以中外专利数据库服务平台CNIPR作为数据源,分别从局部离群因子算法和社会网络分析方法两个视角对中国风能领域的专利数据进行对比分析,识别中国风能领域的核心技术以及核心技术的发展趋势。[结果/结论]结果显示,局部离群因子算法(LOF)和社会网络分析方法得出的结论基本一致:即中国在风力发电机技术方面一直保持优势,未来的发展潜力集中在风能照明装置及系统,验证了局部离群因子算法在探测核心技术及核心技术发展趋势方面的有效性。

[ Purpose/Significance] The paper aims to verify the effectiveness of LOF algorithm in the detection of the core technology＇s development trend and thus promote the research of patent analysis. [ Method/Process ] Taking patent database CNIPR as patent data source, the paper conducts a contrastive analysis between LOF algorithm and the social network analysis method, identifying the core technology and the core teclmology＇s development trend for wind energy in China. [ Result/Conclusion] The contrastive analysis result shows a consistency of the two different methods of LOF algorithm and the social network analysis method： China always has the advantage in wind motor and will focus on the lighting devices and equipment in the future. The effectiveness of LOF algorithm in the detection of the core technology＇s development tendency is verified.