基于SVM和Co-seMLP的文档问答方法

2018 14th International Conference on Computational Intelligence and Security (CIS) Pub Date : 2018-11-01 DOI:10.1109/CIS2018.2018.00046

Xiaoan Liu, Tao Peng

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引用次数: 0

摘要

在本文中，我们描述了我们在nlpcc - iccppol 2017中中文开放域问答DBQA共享任务的特征和模型。通过对任务和数据集的分析，提取出8个特征，然后训练出4个模型。最后，我们的模型得到了一个结果，其中MRR得分为0.494292,MAP得分为0.491736。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2018 14th International Conference on Computational Intelligence and Security (CIS)

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