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Rough Set and Artificial Neural Network Approach to Computational Stylistics

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Emerging Paradigms in Machine Learning

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 13))

Introduction

Computational stylistics or stylometry is a study on writing styles. Through linguistic analysis it yields observations on stylistic characteristics for authors, expressed in terms of quantifiable measures. These measures can be exploited for characterisation of writers, finding some similarities and differentiating features amongst their styles, for authorship attribution, and for recognition of documents based not on their topic, which is so common, but style. Stylistic analysis belongs with text mining, data mining, information retrieval, but also pattern recognition [4].

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Urszula StaƄczyk

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  1. Urszula StaƄczyk
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Correspondence to Urszula StaƄczyk .

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Editors and Affiliations

  1. Deptartment of Applied Computer Science, University of Winnipeg, 515 Portage Avenue, Winnipegg, R3B 2E9, Canada

    Sheela Ramanna

  2. , School of Electrical and Information, University of South Australia, Adelaide, SA 5095, Australia

    Lakhmi C Jain

  3. KES International, Shoreham-by-sea, BN43 9AF, United Kingdom

    Robert J. Howlett

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StaƄczyk, U. (2013). Rough Set and Artificial Neural Network Approach to Computational Stylistics. In: Ramanna, S., Jain, L., Howlett, R. (eds) Emerging Paradigms in Machine Learning. Smart Innovation, Systems and Technologies, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28699-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-28699-5_17

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