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 …

The exponential growth of the internet has led to a great deal of interest in developing useful
and efficient tools and software to assist users in searching the Web. Document retrieval …

With the increasing availability of electronic documents and the rapid growth of the World
Wide Web, the task of automatic categorization of documents became the key method for …

In text classification most techniques use bag-of-words to represent documents. The main
problem is to identify what words are best suited to classify the documents in such a way as …

Supervised machine learning studies are gaining more significant recently because of the
availability of the increasing number of the electronic documents from different resources …

In this paper, a new feature selection technique called Term-Class Weight-Inverse-Class
Frequency is proposed for the purpose of text classification. The technique is based on …

Training data matrix used for classification of text documents to multiple categories is
characterized by large number of dimensions while the number of manually classified …

Text classification is used to classify the document of similar types. Text classification can be
also performed under supervision ie it is an supervised leaning technique Text classification …

Several text mining techniques have been proposed to deal with the huge number of textual
documents that are available and that have been published nowadays. Mainly classification …

This study presents a new framework for termset selection and weighting. The proposed
framework is based on employing the joint occurrence statistics of pairs of terms for termset …