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Adaptive weights clustering of research papers

机译:自适应权重的聚类研究论文

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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-Universitat 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-means or CLUTO reveals excellent performance of AWC.
机译:凝胶的分类系统是一个标准的方法分配经济关键主题的文章他们在大部分更容易检索现在大量的文学作品。(《经济文献)的作者(年代)轴承不佳的风险任务。合作研究中心从我们采用一个新的Humboldt-Universitat祖茂堂柏林自适应聚类技术来识别可说明的凝胶(子)集群。自适应加权聚类(风能网)是可用的http://www.quantlet.de/和基于这个想法局部加权每一点(文档,文摘)集群成员。与k - means或CLUTO揭示风能网的性能优良。

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