Adaptive weights clustering of research papers - Larisa Adamyan; Kirill Efimov; Cathy Yi-hsuan Chen; Wolfgang Karl Härdle (Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, 2017)
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: C32; C55; C58; G11; G17; 330; Clustering; JEL system; Adaptive algorithm; Economic articles; Nonparametric