Dependency-based Discourse Parser for Single-Document Summarization

Yasuhisa Yoshida, Jun Suzuki, Tsutomu Hirao, Masaaki Nagata
2014 Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)  
The current state-of-the-art singledocument summarization method generates a summary by solving a Tree Knapsack Problem (TKP), which is the problem of finding the optimal rooted subtree of the dependency-based discourse tree (DEP-DT) of a document. We can obtain a gold DEP-DT by transforming a gold Rhetorical Structure Theory-based discourse tree (RST-DT). However, there is still a large difference between the ROUGE scores of a system with a gold DEP-DT and a system with a DEP-DT obtained from
more » ... n automatically parsed RST-DT. To improve the ROUGE score, we propose a novel discourse parser that directly generates the DEP-DT. The evaluation results showed that the TKP with our parser outperformed that with the state-of-the-art RST-DT parser, and achieved almost equivalent ROUGE scores to the TKP with the gold DEP-DT.
doi:10.3115/v1/d14-1196 dblp:conf/emnlp/YoshidaSHN14 fatcat:ronkily6ufhizjcad2rfjhlwt4