Authorship Attribution in Portuguese Using Character N-grams
Markov, Ilia, Baptista, Jorge, Pichardo-Lagunas, Obdulia · Acta Polytechnica Hungarica · 2017
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.