A text mining framework to support nano science and technology management

被引:0
|
作者
Yuan Junpeng [1 ]
Huang Jin [2 ]
Zhu Donghua [3 ]
Bao Hailong [4 ]
Yang Chunning [5 ]
机构
[1] Tsinghua Univ, Sch Publ Policy & Management, Beijing 100084, Peoples R China
[2] NanJing Artillery Acad, Nanjing 211132, Jiangsu, Peoples R China
[3] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[4] Ctr China Natl Def, Sci & Technolog Informat, Beijing 100036, Peoples R China
[5] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper addresses how to inform nano science and technology management by mining a particularly rich information resource - the publicly accessible databases on nano fields. Empirical bibliometrics, technology forecast, technology assessment and competitive technical intelligence are not well utilized in technology management. Three factors could enhance managerial utilization: capability to exploit huge volumes of available information, ways to do so very quickly and informative representations that help manage emerging technologies. In this paper a framework based on text mining techniques is proposed to discover useful intelligence from the large body of nano's electronic text sources. This intelligence is a prime requirement for successful S&T management. After that the proposed method is applied to nano technology to give an empirical study.
引用
收藏
页码:2086 / +
页数:3
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