Authors:
Panagiotis Satos
1
and
Chrysostomos Stylios
1
;
2
Affiliations:
1
Department of Informatics and Telecommunications, University of Ioannina, Arta, Greece
;
2
Industrial Systems Institute, Athena Research Center, Patras, Greece
Keyword(s):
n-grams, Multinomial Naïve Bayes Classifier, Text Mining, Machine Learning, Natural Language Processing, Theological Texts, Identifying Authors.
Abstract:
This work proposes a methodology consisting of splitting and pre-processing of Koine Greek dialect texts, examining word n-grams, character n-grams, multiple-length grams, and then suggests the best value for n of n-grams. The Multinomial Naïve Bayes Classifier is used along with the n-grams to identify the author of the text “Epistle to the Hebrews” between Paul and Luke, who are considered the most likely authors of this Epistle. In order to create a balanced dataset, the texts of Apostle Paul’s Epistles and the book “Acts of the Apostles” by Luke the Evangelist are used. This work aims to identify the author of the text “Epistle to the Hebrews” and reply to the theological question about its paternity.