Automatic text categorization is an important research area and has a potential for many text-
based applications including text routing and filtering. Typical text classifiers learn from …

Text categorization is the task of discovering the category or class text documents belongs
to, or in other words spotting the correct topic for text documents. While there today exists …

Typical text classifiers learn from example and training documents that have been manually
categorized. In this research, our experiment dealt with the classification of news wire …

Automated text categorization is a supervised learning task, defined as assigning category
labels to new documents based on likelihood suggested by a training set of labeled …

Automatic text categorization has always been an important application and research topic
since the inception of digital documents. Today, text categorization is a necessity due to the …

Supervised text categorization is a machine learning task where a predefined category label
is automatically assigned to a previously unlabelled document based upon characteristics of …

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 …

Text categorization–the assignment of natural language texts to one or more predefined
categories based on their content–is an important component in many information …

The automated categorisation (or classification) of texts into topical categories has a long
history, dating back at least to 1960. Until the late'80s, the dominant approach to the problem …

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 …