The automated categorization (or classification) of texts into predefined categories has
witnessed a booming interest in the last 10 years, due to the increased availability of …

In recent years growth of digital data is increasing, knowledge discovery and data mining
have attracted great attention with coming up need for turning such data into useful …

Text mining is a new and exciting area of computer science research that tries to solve the
crisis of information overload by combining techniques from data mining, machine learning …

Automated feature selection is important for text categorization to reduce feature size and to
speed up learning process of classifiers. In this paper, we present a novel and efficient …

Many data mining techniques have been proposed for mining useful patterns in text
documents. However, how to effectively use and update discovered patterns is still an open …

As the Web continues to grow, it has become increasingly difficult to search for relevant
information using traditional search engines. Topic-specific search engines provide an …

In this paper, we present a Bayesian classification approach for automatic text categorization
using class-specific features. Unlike conventional text categorization approaches, our …

This paper presents the design and evaluation of a text categorization method based on the
Hierarchical Mixture of Experts model. This model uses a divide and conquer principle to …

Motivation: Controlled vocabularies such as the Medical Subject Headings (MeSH)
thesaurus and the Gene Ontology (GO) provide an efficient way of accessing and organizing …

Automatic categorization is the only viable method to deal with the scaling problem of the
World Wide Web (WWW). In this paper, we propose a news web page classification method …