Combining Event-level and Cross-event Semantic Information for Event-Oriented Relation Classification by SCNN

摘要：

　　Previous researches on event relation classification primarily rely on lexical and syntactic features.In this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-event semantic features for event relation classification.On the one hand,the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation samples.On the other hand,the utilization and combination of event-level and cross-event semantic information help improve relation classification.The experimental results show that our approach outperforms the state of the art.

关键词： Event Relation Classification Semantic Information Frame Embedding SCNN

作者: Siyuan Ding Yu Hong Shanshan Zhu Jianmin Yao Qiaoming Zhu

作者单位: Provincial Key Laboratory of Computer Information Processing Technology,Soochow University,Suzhou,China

会议类型: 国内会议

会议名称: 第十五届全国计算语言学学术会议(CCL2016)暨第四届基于自然标注大数据的自然语言处理国际学术研讨会(NLP-NABD-2016)

会议地点: 烟台

会议语种:英文

页码: 1-9

在线出版日期: 2016-10-14（万方平台首次上网日期，不代表论文的发表时间）