2017/08/19 by Shamima Mithun, Leila Kosseim, Mithun, Shamima +1
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling #cs.CL
paper · pdf · doi:10.48550/arxiv.1708.05803
In Proceedings of the 6th International Joint Conference on Natural Language Processing (IJCNLP 2013), pages 1401-1409, October 2013, Nagoya, Japan
arxiv created 2017/08/19 · openalex publication_date 2017/08/19 · arxiv updated 2017/08/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.