TY - JOUR
T1 - Authorship attribution in portuguese using character N-grams
AU - Markov, Ilia
AU - Baptista, Jorge
AU - Pichardo-Lagunas, Obdulia
N1 - Publisher Copyright:
© 2017, Budapest Tech Polytechnical Institution. All rights reserved.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Authorship attribution
KW - Character n-grams
KW - Computational linguistics
KW - Machine learning
KW - Portuguese
KW - Stylometry
UR - http://www.scopus.com/inward/record.url?scp=85035065760&partnerID=8YFLogxK
U2 - 10.12700/APH.14.3.2017.3.4
DO - 10.12700/APH.14.3.2017.3.4
M3 - Artículo
SN - 1785-8860
VL - 14
SP - 59
EP - 78
JO - Acta Polytechnica Hungarica
JF - Acta Polytechnica Hungarica
IS - 3
ER -