Feature selection and extraction are frequently used solutions to overcome the curse of
dimensionality in text classification problems. We introduce an extraction method that …

Day by day the number of text documents in digital form is increasing. Text classification is
used to organize these text documents. However, text classification has the problem of high …

1. Background With the immense growth of online information due to Internet, text-
categorization has become a very significant technology to classify a large number of …

Text classification, as part of text mining domain, is the problem of classifying text documents
into a set of predefined classes. After extracting the features, documents are represented as …

In recent years, there has been an exponential growth in the number of complex documents
and texts that require a deeper understanding of machine learning methods to be able to …

Text classification is used to organize documents in a predefined set of classes. It is very
useful in Web content management, search engines; email filtering, etc. Text classification is …

The rapid growth of World Wide Web has led to explosive growth of information. As most of
information is stored in the form of texts, text mining has gained paramount importance. With …

With a growing amount of electronic documents available, there is a need to classify
documents automatically. In growing text classification applications, important-term selection …

This paper proposes a new feature selection score for text classification. The value that this
score assigns to each feature has an appealing Bayesian interpretation, being the posterior …

Traditionally, the best number of features is determined by the so-called “rule of thumb”, or
by using a separate validation dataset. We can neither find any explanation why these lead …