Measuring the Effect of Discourse Relations on Blog Summarization
August 19, 2017 ยท Declared Dead ยท ๐ International Joint Conference on Natural Language Processing
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Authors
Shamima Mithun, Leila Kosseim
arXiv ID
1708.05803
Category
cs.CL: Computation & Language
Citations
2
Venue
International Joint Conference on Natural Language Processing
Last Checked
5 months ago
Abstract
The work presented in this paper attempts to evaluate and quantify the use of discourse relations in the context of blog summarization and compare their use to more traditional and factual texts. Specifically, we measured the usefulness of 6 discourse relations - namely comparison, contingency, illustration, attribution, topic-opinion, and attributive for the task of text summarization from blogs. We have evaluated the effect of each relation using the TAC 2008 opinion summarization dataset and compared them with the results with the DUC 2007 dataset. The results show that in both textual genres, contingency, comparison, and illustration relations provide a significant improvement on summarization content; while attribution, topic-opinion, and attributive relations do not provide a consistent and significant improvement. These results indicate that, at least for summarization, discourse relations are just as useful for informal and affective texts as for more traditional news articles.
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