Distinction of The Authors of Texts Using Multilayered Feedforward Neural Networks
Abstract
This paper proposes a means of using a multilayered feedforward neural network to identify the author of a text. The network has to be trained where multilayer feedforward neural network as a powerful scheme for learning complex input-output mapping have been used in learning of the average number of words and average characters of words in a paragraphs of an author. The resulting training information we get will be used to identify the texts written by authors. The computational complexity is solved by dividing it into a number of computationally simple tasks where the input space is divided into a set of subspaces and then combining the solutions to those tasks. By this, we have been able to successfully distinguish the books authored by Leo Tolstoy, from the ones authored by George Orwell and Boris Pasternak.
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PDFDOI: http://dx.doi.org/10.21533/scjournal.v1i1.82
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Copyright (c) 2015 SouthEast Europe Journal of Soft Computing
ISSN 2233 -1859
Digital Object Identifier DOI: 10.21533/scjournal
This work is licensed under a Creative Commons Attribution 4.0 International License