A Chinese Question Answering Approach Integrating Count-based and Embedding-based Features

摘要：

　　Document-based Question Answering system,which needs to match semantically the short text pairs,has gradually become an important topic in the fields of natural language processing and informa-tion retrieval.Question Answering system based on English corpus has developed rapidly with the utilization of the deep learning technology,whereas an effective Chinese-customized system needs to be paid more attention.Thus,we explore a Question Answering system which is characterized in Chinese for the QA task of NLPCC.In our approach,the ordered sequential information of text and deep matching of semantics of Chinese textual pairs have been captured by our count-based traditional methods and embedding-based neural network.The ensemble strategy has achieved a good performance which is much stronger than the provided baselines.

关键词： Question Answer DBQA semantic matching Chinese text

作者: Benyou Wang Jiabin Niu Liqun Ma Yuhua Zhang Lipeng Zhang Jingfei Li Peng Zhang Dawei Song

作者单位: Tianjin Key Laboratory of Cognitive Computing and Application,School of Computer Science and Technol Tianjin Key Laboratory of Cognitive Computing and Application,School of Computer Science and Technol

会议类型: 国际会议

会议名称: 第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)

会议地点: 昆明

会议语种:英文

页码: 1-8

在线出版日期: 2016-12-02（万方平台首次上网日期，不代表论文的发表时间）