A common way of performing Feature Selection in Text Categorization consists in keeping
the features with highest score according to certain measures, like linear ones which have …

Feature selection has been an interesting issue in text categorization up to now. Previous
works in feature selection often used filter model in which features, after ranked by a …

Text Categorization, which consists of automatically assigning documents to a set of
categories, usually involves the management of a huge number of features. Most of them are …

Text categorisation relies heavily on feature selection. Both the possible reduction in
dimensionality as well as improvements in classification performance are highly desirable …

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 …

Feature selection plays a vital role in text categorisation. A range of different methods have
been developed, each having unique properties and selecting different features. We show …

This paper presents a novel local feature selection approach for text categorization. It
constructs a feature set for each category by first selecting a set of terms highly indicative of …

To improve scalability of text categorization and reduce over-fitting, it is desirable to reduce
the number of words used for categorisiation. Further, it is desirable to achieve such a goal …

Text categorization (TC) is a problem of assigning a document into predefined classes. One
of the most important issues in TC is feature selection. In this paper, we propose a new …

Text categorization, which consists of automatically assigning documents to a set of
categories, usually involves the management of a huge number of features. Most of them are …