An Empirical Text Categorizing Computational Model Based on Stylistic Aspects

  • Authors:
  • S. E. Michos;E. Stamatatos;N. Fakotakis;G. Kokkinakis

  • Affiliations:
  • -;-;-;-

  • Venue:
  • ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
  • Year:
  • 1996

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Abstract

The presented work is strongly motivated by the need of categorizing unrestricted texts in terms of functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, it is given a three-level description of FS that comprises: (a) the basic categories of FS, (b) the main features that characterize each one of the above categories, and (c) the linguistic identifiers that act as style markers in texts for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically-driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real-world texts, and recognition of style shift between adjacent portions of text.