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A SVM and Co-seMLP Integrated Method for Document-Based Question Answering

机译:基于SVM和Co-seMLP的基于文档的问答集成方法

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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.
机译:在本文中,我们描述了NLPCC-ICCPOL 2017中的中文开放域问答DBQA共享任务的特征和模型。在对任务和数据集进行分析之后,提取了8个特征,然后训练了4个模型。最终,我们的模型获得了一个结果,其中MRR得分为0.494292,MAP得分为0.491736。

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