Back to Search
Start Over
Adaptive weights clustering of research papers
- Source :
- Digital Finance. 2:169-187
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- The JEL classification system is a standard way of assigning key topics to economic articles 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 the Collaborative Research Center from Humboldt-Universität zu Berlin we employ a new adaptive clustering technique to identify interpretable JEL (sub)clusters. The proposed Adaptive Weights Clustering (AWC) is available on http://www.quantlet.de/ and is based on the idea of locally weighting each point (document, abstract) in terms of cluster membership. Comparison with $$k$$ k -means or CLUTO reveals excellent performance of AWC.
- Subjects :
- JEL system
Adaptive algorithm
Point (typography)
Computer science
330 Wirtschaft
05 social sciences
Nonparametric statistics
020206 networking & telecommunications
02 engineering and technology
computer.software_genre
Clustering
Weighting
0502 economics and business
ddc:330
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
Economic articles
Nonparametric
Data mining
050207 economics
Cluster analysis
computer
Research center
Subjects
Details
- ISSN :
- 25246186 and 25246984
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Digital Finance
- Accession number :
- edsair.doi.dedup.....ede81b1308c39c456f5f7e0f88a1bda8
- Full Text :
- https://doi.org/10.1007/s42521-020-00017-z