In this paper, a simple and efficient symbolic text classification is presented. A text document
is represented by the use of interval valued symbolic features. Subsequently, a new feature …

In this paper, we propose a new method of representing documents based on clustering of
term frequency vectors. For each class of documents we propose to create multiple clusters …

This paper presents a novel method of representing a text document by the use of interval
valued symbolic features. A method of classification of text documents based on the …

In this paper, we present symbolic classifiers to classify text documents. We propose to use
cluster based symbolic representation followed by symbolic feature selection methods to …

In this paper, we propose a new method of representing text documents based on feature
clustering approach. The proposed representation method is very powerful in reducing the …

Training a system using a small number of instances to obtain accurate recognition/
classification is a crucial need in document classification domain. The one-class …

Text classification is the process of assigning a predefine class or category to an anonymous
text based on its content. It is an important task in text mining. Several Text classification …

Text classification technologies rely heavily on the distribution of features, and the selection
of discriminant features with regards to the classes as the main basis for classification. In this …

Text categorization is the process of assigning documents to a set of previously fixed
categories. In this paper we develop an optimal SVM algorithm for text classification via …

In this paper, we introduce an alternative framework for selecting a most relevant subset of
the original set of features for the purpose of text categorization. Given a feature set and a …