Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/169203
Authors: 
Adamyan, Larisa
Efimov, Kirill
Chen, Cathy Yi-hsuan
Härdle, Wolfgang
Year of Publication: 
2017
Series/Report no.: 
SFB 649 Discussion Paper 2017-013
Abstract: 
The JEL classification system is a standard way of assigning key topics to economic articles in order to make them more easily retrievable in the bulk of nowadays massive literature. Usually the JEL (Journal of Economic Literature) is picked by the author(s) bearing the risk of suboptimal assignment. Using the database of a Collaborative Research Center from Humboldt-Universität zu Berlin and Xiamen University, China we employ a new adaptive clustering technique to identify interpretable JEL (sub)clusters. The proposed Adaptive Weights Clustering (AWC) is available on www.quantlet.de and is based on the idea of locally weighting each point (document, abstract) in terms of cluster membership. Comparison with k-means or CLUTO reveals excellent performance of AWC.
Subjects: 
Clustering
JEL system
Adaptive algorithm
Economic articles
Nonparametric
JEL: 
C32
C55
C58
G11
G17
Document Type: 
Working Paper

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