Adaptive weights clustering of research papers

Larisa Adamyan, Kirill Efimov, Cathy Yi-hsuan Chen and Wolfgang Härdle

No 2017-013, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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 (search for similar items in EconPapers)
JEL-codes: C32 C55 C58 G11 G17 (search for similar items in EconPapers)
Date: 2017
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Journal Article: Adaptive weights clustering of research papers (2020)
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