The amount of texts available in digital form has dramatically increased, giving rise to the need of fast text classifiers. The tasks involved can be parallelized and distributed in a grid environment. This paper reports a study conducted on Reuters-21578 corpus, using a SVM learning machine. The task of text categorization is distributed in several platforms. The results achieved are very promising for speeding-up text categorization tasks and are valid independently of the learning machine.
['Catarina Silva', 'Bernardete Ribeiro', 'Uroš Lotrič']
Speeding-up text categorization in a grid computing environment