摘要
[目的/意义]技术机会识别是企业技术创新活动得以顺利开展的重要前提,及时发现和把握有价值的技术机会对技术创新突破意义重大.[方法/过程]从主题挖掘与专利评估的视角提出一种技术机会识别方法,首先应用主题模型识别技术领域涵盖的技术主题并进行专利聚类;其次在技术主题层面展开细粒度分析,综合考虑技术机会应具备前沿性、价值性和时效性的重要特性,采用突变级数法和离群因子算法评估技术主题中的高价值专利和离群专利形成核心专利集,并计算每个技术主题的专利平均年龄;最后,将技术主题中的核心专利占比和专利平均年龄作为核心指标绘制技术机会识别地图,用于识别技术机会.[结果/结论]以智慧农业领域为例,对所提方法进行实证,识别智慧农业领域的5个技术机会,为创新主体的技术研发提供决策支持.但识别结果的定量验证以及融合多源数据进行技术机会识别有待进一步探索.
[Purpose/Significance]The identification of technological opportunities is an important prerequisite for the smooth development of technological innovation activities of enterprises.It is of great significance to discover and grasp valuable technological opportunities in time for technological innovation breakthrough.[Method/Process]In this paper,a technology opportunity identification method was proposed from the perspective of topic mining and patent evaluation.Firstly,the technology topics covered by the technology field were identified by the topic model and the patent clustering was carried out.Then,the fine-grained analysis was carried out at the level of technology topics.This paper comprehensively considers the three important characteristics of technological opportunities:frontier,value and timeliness.The mutation progression method and outlier factor algorithm were used to evaluate the high-value patents and outlier patents in the technology topics to form the core patent set,and the average age of patents for each technology topic was calculated.Finally,the proportion of core patents in the technology topic and the average age of patents were taken as the core indicators to draw the technology opportunity identification map to identify the opportunities in the technology field.[Result/Conclusion]Taking the field of smart agriculture as an example,the proposed method is empirically demonstrated,and five technological opportunities in the field of smart agriculture are identified,which provides decision support for the technology R&D of innovation subjects.However,the quantitative verification of identification results and the fusion of multi-source data for technical opportunity identification need to be further explored.
作者
宋凯
冉从敬
Song Kai;Ran Congjing(Shandong Normal University Library,Jinan 250358;School of Information Management,Wuhan University,Wuhan 430072)
出处
《图书情报工作》
CSSCI
北大核心
2023年第3期61-71,共11页
Library and Information Service
基金
国家社会科学基金重大项目“大数据主权安全保障体系建设研究”(项目编号:21&ZD169)研究成果之一。
关键词
主题模型
价值评估
技术机会
智慧农业
topic model
value evaluation
technology opportunity
smart agriculture
作者简介
宋凯,馆员,博士;通信作者:冉从敬,教授,博士生导师,E-mail:rancongjing@163.com。
