摘要
专利信息作为目前国际知识产权中科技含量最高的存在,是国家和企业获取竞争优势最全面的技术情报来源。使用专利数据网的数据信息作为测试数据,采用K-means算法,针对专利文本数据进行聚类分析,旨在找出隐含在专利数据信息中不容易被直观发现或直接统计得出的数据情报信息。通过深入挖掘专利信息,提高专利信息利用率,使之转换为具有实际价值的情报信息,有效解决了对专利信息利用不足的问题。
Patent information is the most comprehensive source of technical information for countries and enterprises to obtain competitive advantages.In this paper,the data information of the patent data network is used as the test data,and K-means algorithm is adopted to conduct clustering analysis on the patent text data.The aim is to find out the data intelligence information which is hidden in the patent data information and not easy to be found directly.Through deep mining of patent information,improving the utilization rate of patent information,transforming it into information with practical value,the problem of insufficient utilization of patent information is effectively solved.
作者
薛淑晖
王丽
吴海涛
XUE Shuhui;WANG Li;WU Haitao(Nanjing Institute of Technology,Nanjing 211167,China)
出处
《现代信息科技》
2020年第5期85-86,89,共3页
Modern Information Technology
基金
江苏省高等学校大学生创新创业训练计划项目(201911276073Y)。
