Implementing a characterization of genre for automatic genre identification of web pages

Authors:
Marina Santini;Richard Power;Roger Evans
Affiliations:
University of Brighton, UK;Open University, UK;University of Brighton, UK
Venue:
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Year:
2006

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Abstract

In this paper, we propose an implementable characterization of genre suitable for automatic genre identification of web pages. This characterization is implemented as an inferential model based on a modified version of Bayes' theorem. Such a model can deal with genre hybridism and individualization, two important forces behind genre evolution. Results show that this approach is effective and is worth further research.