The aim of text document classification is to automatically group a document to a predefined
class. The main problem of document classification is high dimensionality and sparsity of the …

Effective feature selection methods are essential for improving the accuracy and efficiency of
text categorization. Motivated by document frequency, we proposed a new filter-based …

With the ever-increasing number of digital documents, the ability to automatically classify
those documents both quickly and accurately is becoming more critical and difficult. A text …

In the present scenario, millions of internet users are contributing a huge amount of data in
the form of unstructured text documents. In text classification, the high dimensional feature …

This paper presents a new feature selection algorithm with the category information analysis
in text classification. The algorithm obscure or reduce the noises of text features by …

The problem of feature selection is to find a subset of features for optimal classification. A
critical part of feature selection is to rank features according to their importance for …

Feature selection plays an important role in text categorization. Automatic feature selection
methods such as document frequency thresholding (DF), information gain (IG), mutual …

High dimensionality of the feature space is one of the most important concerns in text
categorization problems, and feature selection is widely used for reducing the …

Text classification is the problem of classifying a set of documents into a pre-defined set of
classes. A major problem with text classification problems is the high dimensionality of the …

The high dimensionality of data is a great challenge for effective text classification. Each
document in a document corpus contains many irrelevant and noisy information which …