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 …

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 …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

This paper is a comparative study of feature selection methods in statistical learning of text
categorization. The focus is on aggressive dimensionality reduction. Five methods were …

This paper presents an approach to automatically optimizing the retrieval quality of search
engines using clickthrough data. Intuitively, a good information retrieval system should …

This paper reports a controlled study with statistical significance tests on five text
categorization methods: the Support Vector Machines (SVM), a k-Nearest Neighbor (kNN) …

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 …

Text Classification, or the task of automatically assigning semantic categories to natural
language text, has become one of the key methods for organizing online information. Since …

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 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 …