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New Technology of Library and Information Service  2015, Vol. 31 Issue (7-8): 89-96    DOI: 10.11925/infotech.1003-3513.2015.07.12
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Research on Comparison Method of Scientific Funding Layout——Take NSF and EU FP Grants for Instance
Chen Ting, Han Tao, Li Zexia, Li Guopeng, Wang Xiaomei
National Science Library, Chinese Academy of Sciences, Beijing 100190, China
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[Objective] This study targets to improve the ability to discover research layout of funding agencies based on their funding application documents. [Methods] The K-means++ clustering method is proposed to analyse the funding direction and main focus based on multiple sources of funding application documents. [Results] After validation and a case study based on the funding application abstracts from NSF and FP, it is discovered that single-word feature is more accurate than multi-word feature in the K-means++ clustering. If only keep the essential contents of application abstrcts as analysis documents, the accuracy of the K-means++ clustering is significantly improved. [Limitations] Data cleaning of the funding application documents is not fully automated. Adjustment of clustering parameters need to be manually controlled. [Conclusions] The K-means++ clustering of funding application documents is a practicable method by validation and case study. Research layout differences in agencies' funding trends are discovered and could be helpful for scientific management and policy decision.

Received: 18 December 2014      Published: 25 August 2015
:  G250  

Cite this article:

Chen Ting, Han Tao, Li Zexia, Li Guopeng, Wang Xiaomei. Research on Comparison Method of Scientific Funding Layout——Take NSF and EU FP Grants for Instance. New Technology of Library and Information Service, 2015, 31(7-8): 89-96.

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