In this paper, we compare several aspects related to automatic text categorization which
include document representation, feature selection, three classifiers, and their application to …

In this informative age, we find many documents are available in digital forms which need
classification of the text. For solving this major problem present researchers focused on …

We describe the results of extensive machine learning experiments on large collections of
Reuters' English and German newswires. The goal of these experiments was to …

The automated categorization of texts into predefined categories has witnessed a booming
interest in the last 10 years, due to the increased availability of documents in digital form and …

This paper focuses on a comparative evaluation of a wide-range of text categorization
methods, including previously published results on the Reuters corpus and new results of …

This article reports on our experiments and results on the effectiveness of different feature
sets and information fusion from some combinations of them in classifying free text …

Text classification research and practice has exploded in the past decade_ This work has
been pursued under a variety of headings (text categorization, automated indexing …

Categorization of texts into topical categories has gained booming interest over the past few
years. There is a growing need for tools that help in finding, filtering and managing the …

The effect of selecting varying numbers and kinds of features for use in predicting category
membership was investigated on the Reuters and MUC-3 text categorization data sets …

This paper describes Olex, a novel method for the automatic induction of rule-based text
classifiers. Olex supports a hypothesis language of the form" if T 1 or hellip or T n occurs in …