%0 Journal Article
%T Global Nanotechnology Research Literature<br>全球纳米技术研究文献计量分析
%A Ronald N Kostoff
%A Raymond G Koytcheff
%A Clifford GY Lau Office of Naval Research
%A Arlington
%A VA
%A USA Institute for Defense Analyses
%A Alexandria
%A VA
%A USA
%A <br>Ronald N. Kostoff
%A Raymond G. Koytcheff
%A Clifford G.Y. Lau
%J 科学观察
%D 2007
%I 
%X Text mining was used to extract technical intelligence from the global open nanotechnology and nanoscience research literature. An extensive nanotechnology/nanosciene-focuse query (300 term) was applied to the SCI/SSCI database. A novel addition was the use of phrase auto correlation maps to show technical thrust areas based on phrase co-occurrence in Abstracts, and the use of phrase-phrase cross-correlation maps to show technical thrust areas based on phrase relations due to the sharing of common co-occurring phrases. The use of factor matrices quantified further the strength of the linkages among institutions and among countries, and validated the co-publishing networks shown graphically on the maps.
%K nanoparticle
%K nanotube
%K nanotechnology
%K text mining
%K bibliometrics
%K document clustering<br>纳米颗粒
%K 纳米管
%K 纳米技术
%K 文本挖掘
%K 文献计量
%K 文献聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=96E6E851B5104576C2DD9FC1FBCB69EF&jid=482FA29C88ACD98DBC7B667E04441E34&aid=13E6E6D34E13D795FDABC6F5A06A77C5&yid=A732AF04DDA03BB3&vid=0B39A22176CE99FB&iid=0B39A22176CE99FB&sid=CA4FD0336C81A37A&eid=F3090AE9B60B7ED1&journal_id=1673-5668&journal_name=科学观察&referenced_num=1&reference_num=1