Authorship Categorization With Neural Network

Abstract

This paper explores the use of neural networks in author classification. Also exploring the effect of stylometry is another aim of the research. Choosing the algorithm and descriptors are important issues in the research. In this paper methods for the multi-topic machine learning of an authorship attribution classifier were investigated using texts from novels as the data set. Artificial neural network is proposed to classify the texts of authors using a set of lexical descriptors and feed-forward neural network using back propagation. The result shows that Turkish authors Peyami Safa, Orhan Pamuk and Mustafa Necati Sepetcioglu’s two novels are successfully classified.