%0 Journal Article %A LIU Hang %A LIU Mingtong %A ZHANG Yujie %A XU Jinan %A CHEN Yufeng %T Improved Character-based Chinese Dependency ParsingBased on Stack-Tree LSTM %D 2019 %R %J Journal of Chinese Information Processing %P 10-17 %V 33 %N 1 %X In the character-based Chinese dependency parsing, it is crucial to best utilize the intermediate results of word segmentation, POS tagging and dependency parsing. To fully exploit the dependency subtree information, this paper proposes a novel Stack-Tree LSTM, which is essentially a character-based neural network joint model by integrating subtree feature and POS feature in addition to N-gram feature. Experiments on Penn Chinese Treebank 5 show that our model is comparable to the best results, out-performing other neural joint models. %U http://jcip.cipsc.org.cn/EN/abstract/article_2693.shtml