Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15635
Title: An ontology-based text-mining method to cluster proposals for research project selection
Authors: Ma, J
Xu, W
Sun, YH
Turban, E
Wang, S
Liu, O 
Keywords: Clustering analysis
decision support systems
ontology
research project selection
text mining
Issue Date: 2012
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans, 2012, v. 42, no. 3, 6171866, p. 784-790 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans 
Abstract: Research project selection is an important task for government and private research funding agencies. When a large number of research proposals are received, it is common to group them according to their similarities in research disciplines. The grouped proposals are then assigned to the appropriate experts for peer review. Current methods for grouping proposals are based on manual matching of similar research discipline areas and/or keywords. However, the exact research discipline areas of the proposals cannot often be accurately designated by the applicants due to their subjective views and possible misinterpretations. Therefore, rich information in the proposals' full text can be used effectively. Text-mining methods have been proposed to solve the problem by automatically classifying text documents, mainly in English. However, these methods have limitations when dealing with non-English language texts, e.g., Chinese research proposals. This paper presents a novel ontology-based text-mining approach to cluster research proposals based on their similarities in research areas. The method is efficient and effective for clustering research proposals with both English and Chinese texts. The method also includes an optimization model that considers applicants' characteristics for balancing proposals by geographical regions. The proposed method is tested and validated based on the selection process at the National Natural Science Foundation of China. The results can also be used to improve the efficiency and effectiveness of research project selection processes in other government and private research funding agencies.
URI: http://hdl.handle.net/10397/15635
ISSN: 1083-4427
EISSN: 1083-4419
DOI: 10.1109/TSMCA.2011.2172205
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

26
Last Week
0
Last month
0
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

11
Last Week
0
Last month
1
Citations as of Aug 21, 2017

Page view(s)

47
Last Week
2
Last month
Checked on Aug 21, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.