Abstract
This papers aims to measure the influence of textual genre on the usage of discourse relations and discourse markers. Specifically, we wish to evaluate to what extend the use of certain discourse relations and discourse markers are correlated to textual genre and consequently can be used to predict textual genre. To do so, we have used the British National Corpus and compared a variety of discourse-level features on the task of genre classification. The results show that individually, discourse relations and discourse markers do not outperform the standard bag-of-words approach even with an identical number of features. However, discourse features do provide a significant increase in performance when they are used to augment the bag-of-words approach. Using discourse relations and discourse markers allowed us to increase the F-measure of the bag-of-words approach from 0.796 to 0.878.
Cite
CITATION STYLE
Davoodi, E., Kosseim, L., Bachand, F. H., Laali, M., & Argollo, E. (2018). Classification of textual genres using discourse information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9623 LNCS, pp. 636–647). Springer Verlag. https://doi.org/10.1007/978-3-319-75477-2_46
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