Research profiling: Improving the literature review

被引:146
作者
Porter, AL [1 ]
Kongthon, A
Lui, JC
机构
[1] Georgia Tech Res Inst, Sch Ind & Syst Engn, Atlanta, GA 30332 USA
[2] Georgia Tech Res Inst, Sch Publ Policy, Atlanta, GA 30332 USA
基金
美国国家科学基金会;
关键词
Data Integration; Text Mining; Science Citation Index; Georgia Tech; Data Splitting;
D O I
10.1023/A:1014873029258
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We propose enhancing the traditional literature review through "research profiling". This broad scan of contextual literature can extend the span of science by better linking efforts across research domains. Topical relationships, research trends, and complementary capabilities can be discovered, thereby facilitating research projects. Modem search engine and text mining tools enable research profiling by exploiting the wealth of accessible information in electronic abstract databases such as MEDLINE and Science Citation Index. We illustrate the potential by showing sixteen ways that "research profiling" can augment a traditional literature review on the topic of data mining.
引用
收藏
页码:351 / 370
页数:20
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