Abstract
Analysis, prediction, and recommendation of information about experts are very important tasks for future research planning and strategy establishment. However, it takes much time and efforts even for precise analysis of experts because we need to analyze huge and diverse heterogeneous information. There are several application and tools for supporting analysis about researchers, but they provides fragmentary analysis result based on simple evaluation criteria. Therefore, in this paper, we suggest new researcher evaluation model based on diverse performance evaluation features, named RSW model. By using RSW model, we can analyze and compare researchers in various perspectives. In addition, we can ranked researchers and recommend outstanding collaborator in a specified research field.
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Kim, J. et al. (2014). Diverse Heterogeneous Information Source-Based Researcher Evaluation Model for Research Performance Measurement. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_40
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DOI: https://doi.org/10.1007/978-3-642-40675-1_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40674-4
Online ISBN: 978-3-642-40675-1
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