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Ranking in multi label classification of text documents using quantifiers

机译:使用量化器排名文本文档的多标签分类

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In today's world, many real world examples are based on multi label classification. A single document may belong to a set of class labels simultaneously. The process of ranking i.e. strict ordering of class labels is of great concern here. We have used the concept of quantifiers for ranking of class labels. We have proposed eight new quantifiers, which calculate the degree of membership of class labels of a particular text document. As a result, we are able to perform ranking of class labels in multi label learning. The proposed approach is shown with the help of a case study.
机译:在今天的世界中,许多真实世界的例子是基于多标签分类。单个文档可以同时属于一组类标签。排名的过程I.在阶级标签的严格订购方面是非常关注的。我们使用了量化器的概念来排名课程标签。我们提出了八个新的量词,计算了特定文本文件的类别标签的成员资格。因此,我们能够在多标签学习中执行类别标签的排序。在案例研究的帮助下显示了所提出的方法。

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