Automatic Text Classification of sports blog data

Automatic Text Classification is a semi-supervised machine learning task that automatically assigns a given text document to a set of pre-defined categories based on the features extracted from its textual content. This paper attempts to automatically classify the textual entries made by bloggers on various sports blogs, to the appropriate category of sport by following steps like pre-processing, feature extraction and naïve Bayesian classification. Empirical evaluation of this technique has resulted in a classification accuracy of approximately 87% over the test set. In addition to classifying the textual entries of sports blogs, it is proposed that the extracted features themselves be further classified under more meaningful heads which results in generation of a semantic resource that lends greater understanding to the classification task. This semantic resource can be used for data mining requirements that arise in the future.