Ranking in multi label classification of text documents using quantifiers

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.