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Text classification, which is a sub-field of the natural language processing, is utilized for the solutions of problems in various areas. One of these areas is the author detection in written texts. When a person writes a text, he or she makes several marks due to the spelling characteristics. Author detection or recognition means that ownership of the text is questioned by comparing these spelling features. Different features belonging to the author can be extracted from texts and many comparisons can be made. In this study, author recognition was performed using bigram, trigram and quadrigram frequency property with the Naïve Bayesian approach for decision making. 120 different Turkish books written by 20 Turkish authors in different distributions were studied. Initially, the authors' bigram, trigram and quadrigram frequency properties were extracted from the books. Then, the comparison of the n-grams performances attained by Naïve Bayesian method is examined through this paper.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Samet Kaya
A. GUNES