Teaching Neural Networks to Detect the Authors of Texts Using Lexical Descriptors

Mehmet Can


This paper proposes a means of using an artificial neural network to distinguish the authors of paragraphs. Once the network has been trained, its hidden layer activations are recorded as a representation of the average number of words and average characters of words in a paragraphs of an author. This stored information can then be used to identify the texts written by authors. This computational task is solved by dividing it into a number of computationally simple tasks and then combining the solutions to those tasks. Computational simplicity is achieved by distributing the learning task among a number of experts, which in turn divides the input space into a set of subspaces. The combination of these experts is said to constitute a committee machine. Basically, it fuses knowledge acquired by experts to arrive at an overall decision that is supposedly superior to that attainable by anyone of them acting alone. By this, we succeeded to distinguish the paragraphs authored by Ivo Andrić, from the ones authored by Mehmed Meša Selimović.

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DOI: http://dx.doi.org/10.21533/scjournal.v1i1.75


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Copyright (c) 2015 SouthEast Europe Journal of Soft Computing

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

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