Abstract
Computational stylistics focuses on such description and quantifiable expression of linguistic styles of written documents and their authors that enable their characterisation, comparison, and attribution. Characterisation of a text and its author can yield information about educational experiences, social background, but also about the author gender which can be exploited within the automatic categorisation of texts. This is an example of a classification task with knowledge uncertain and incomplete. Therefore, techniques from the artificial intelligence area are particularly well suited to handle the problem. The paper presents research on application of ANN-based classifier in recognition of the author gender for literary texts, with some considerations on the performance of the classifier when the reduction of characteristic features based on elements of frequency analysis is attempted.
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Stańczyk, U. (2011). Recognition of Author Gender for Literary Texts. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds) Man-Machine Interactions 2. Advances in Intelligent and Soft Computing, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23169-8_25
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DOI: https://doi.org/10.1007/978-3-642-23169-8_25
Publisher Name: Springer, Berlin, Heidelberg
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