1 code implementation • IJCNLP 2019 • Xiao Ding, Kuo Liao, Ting Liu, Zhongyang Li, Junwen Duan
Prior work has proposed effective methods to learn event representations that can capture syntactic and semantic information over text corpus, demonstrating their effectiveness for downstream tasks such as script event prediction.
1 code implementation • COLING 2018 • Junwen Duan, Yue Zhang, Xiao Ding, Ching-Yun Chang, Ting Liu
The model uses a target-sensitive representation of the news abstract to weigh sentences in the news content, so as to select and combine the most informative sentences for market modeling.
no code implementations • NAACL 2018 • Junwen Duan, Xiao Ding, Ting Liu
To address above issues, we propose a reinforcement learning based approach, which automatically induces target-specific sentence representations over tree structures.
no code implementations • COLING 2016 • Xiao Ding, Yue Zhang, Ting Liu, Junwen Duan
Representing structured events as vectors in continuous space offers a new way for defining dense features for natural language processing (NLP) applications.