文献类型：期刊文献

英文题名：A SVM and Co-seMLP integrated method for document-based question answering

作者：Liu, Xiaoan[1]; Peng, Tao[2]

第一作者：Liu, Xiaoan

机构：[1] College of Intellectualized City, Beijing Union University, Beijing, China; [2] College of Robotics, Beijing Union University, Beijing, China

第一机构：北京联合大学

年份：2018

起止页码：179-182

外文期刊名：Proceedings - 14th International Conference on Computational Intelligence and Security, CIS 2018

收录：EI(收录号：20190506451738)

语种：英文

外文关键词：Natural language processing systems

摘要：In this paper, we describe our features and models for Chinese Open-Domain Question Answering DBQA shared task in NLPCC-ICCPOL 2017. After the analysis of task and dataset, 8 features were extracted, and then 4 models were trained. Finally, our model achieves a result, in which MRR score is 0.494292 and MAP score is 0.491736. ? 2018 IEEE.