Ranking in Multi Label Classification of Text Documents Using Quantifiers

被引：0

作者：

Jindal, Rajni ^{[1
]}

Taneja, Shweta ^{[1
]}

机构：

[1] Delhi Technol Univ, Dept Comp Engn, New Delhi 110042, India

来源：

PROCEEDINGS 5TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE 2015) | 2015年

关键词：

Text Mining; Multi label text classification; Ranking; Quantifiers;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：162 / 166

页数：5

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