Journal
SCIENTOMETRICS
Volume 93, Issue 3, Pages 635-644Publisher
SPRINGER
DOI: 10.1007/s11192-012-0766-x
Keywords
Citation impact; Highly cited papers; Soft fuzzy rough set
Funding
- National Natural Science Foundation of China [71003020, 70973031]
- special funds of Central College Basic Scientific Research Bursary [DL11CB09]
- Postdoctoral Science Foundation of Heilongjiang Province
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In this paper, the machine learning tools were used to identify key features influencing citation impact. Both the papers' external and quality information were considered in constructing papers' feature space. Based on the feature space, the soft fuzzy rough set was used to generate a series of associated feature subsets. Then, the KNN classifier was used to find the feature subset with the best classification performance. The results show that citation impact could be predicted by objectively assessed factors. Both the papers' quality and external features, mainly represented as the reputation of the first author, are contributed to future citation impact.
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