This paper proposes a novel method for sentence-level Chinese discourse tree building. The authors
constrcut a Chinese discourse annotated corpus in the framework of Rhetorical Structure Theory, and propose a
ranking-like SVM (SVM-R) model to automatically build the tree structure, which can capture the relative
associated strength among three consecutive text spans rather than only two adjacent spans. The experimental
results show that proposed SVM-R method significantly outperforms state-of-the-art methods in discourse parsing
accuracy. It is also demonstrated that the useful features for discourse tree building are consistent with Chinese
language characteristics.