摘要
科技查新是评估科技创新活动的重要手段,但查新报告的质量受查新员主观因素的影响较大,查新工作也亟须转型,认为基于大数据的LDA主题模型方法可以帮助提高科技查新的权威性,为科技查新的长远发展提供策略参考。本文介绍了LDA主题模型的理论基础及其应用,形成了基于LDA主题模型的科技查新方法,探讨了该方法在不同查新环节的具体应用,并通过实际案例分析了该方法的应用效果。在科技查新工作中引入LDA主题模型方法,可以帮助查新员有效把控查新点,辅助审核员快速审核报告,启发委托人多维科研思考;不仅提高了查新报告的可读性、客观性,还拓展了查新站的深层次情报服务能力,为科技查新工作的转型做好铺垫。
Sci-tech novelty retrieval is an important approach to evaluate scientific and technological innovation activities,but the quality of novelty retrieval report is greatly affected by the subjective factors of novelty searchers,and the sci-tech novelty retrieval work also needs to be transformed.This paper proposed that the LDA topic model based on big data can effectively improve the authority of sci-tech novelty searching,and provide strategic reference for the development of sci-tech novelty retrieval.This paper introduced the theoretical basis and application of LDA topic model,formed a sci-tech novelty search method based on LDA topic model,discussed the specific application of this method in different aspects of novelty search,and analyzed the effect of this method through practical cases.The introduction of LDA subject model method in the sci-tech novelty retrieval can effectively help the novelty searchers to understand the novelty retrieval points,assist the auditor to rapidly review reports and inspire the clients to evaluate scientific research from multiple perspectives.It not only improves the readability and objectivity of the novelty search report,but also explores the in-depth intelligence service capability of the novelty search station,laying a solid foundation for the transformation of the sci-tech novelty retrieval.
作者
李美凝
张芹
张秀美
Li Meining;Zhang Qin;Zhang Xiumei(China University of Petroleum(Beijing)Library)
出处
《图书馆杂志》
CSSCI
北大核心
2020年第10期45-52,62,共9页
Library Journal
关键词
科技查新
LDA
主题模型
主题演化
Sci-tech novelty retrieval
LDA
Topic model
Topic evolution
作者简介
李美凝,女,中国石油大学(北京)图书馆,馆员,硕士。研究方向:石油情报研究、科技查新。作者贡献:论文研究思路设计、论文撰写。E-mail:limeining@cup.edu.cn,北京102249;张芹,女,中国石油大学(北京)图书馆,副研究馆员,博士。研究方向:石油情报分析。作者贡献:论文指导。北京102249;张秀美,女,中国石油大学(北京)图书馆,馆员,硕士。研究方向:计算机技术。作者贡献:数据编程指导。北京102249。
