SFB649DP2017 013
Adaptive weights clustering of research papers
Larisa Adamyan
Kirill Efimov
Cathy Yi-Hsuan Chen
Wolfgang K. Härdle
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.
Keywords:
Clustering, JEL system, Adaptive algorithm, Economic articles, Nonparametric
JEL Classification:
C00