An Introduction to Text Classification

The increased volume of information available in digital form and the need of organizing it has generated and progressively intensified the interest in automatic text categorization. A widely used research approach to this problem is based on machine learning techniques: an inductive process builds a classifier by automatically learning the characteristics of the categories. Machine learning is more portable and less labour-intensive than manual definition of classifiers. This essay provides an account of the most prominent features of the machine learning approach to text classification, including data preparation, attribute extraction and selection, learning algorithms and kernel methods, performance measures, and availability of training corpora.