The current state-of-the-art single-document 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 an 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.
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