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.
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CITATION STYLE
Santini, M., Power, R., & Evans, R. (2006). Implementing a characterization of genre for automatic genre identification of web pages. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Main Conference Poster Sessions (pp. 699–706). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1273073.1273163
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