Authorship attribution in portuguese using character N-grams

Markov, Ilia; Baptista, Jorge; Pichardo-Lagunas, Obdulia

http://hdl.handle.net/10400.1/11987

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Authors

Markov, Ilia

Baptista, Jorge

Pichardo-Lagunas, Obdulia

Abstract(s)

For the Authorship Attribution (AA) task, character n-grams are considered among the best predictive features. In the English language, it has also been shown that some types of character n-grams perform better than others. This paper tackles the AA task in Portuguese by examining the performance of different types of character n-grams, and various combinations of them. The paper also experiments with different feature representations and machine-learning algorithms. Moreover, the paper demonstrates that the performance of the character n-gram approach can be improved by fine-tuning the feature set and by appropriately selecting the length and type of character n-grams. This relatively simple and language-independent approach to the AA task outperforms both a bag-of-words baseline and other approaches, using the same corpus.