We propose the use of fine-grained part-of-speech (POS) tags as discriminatory attributes for automatic genre classification and report empirical results from an experiment that indicate substantial accuracy gain by such features over the conventional bag-of-words approach through word unigrams.
this paper reports our research to investigate the performance of a fine-grained tag set when tested with the British component of the International Corpus of English.