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

被引：1

作者：

Liu Xiaoan ^{[1
]}

Peng Tao ^{[2
]}

机构：

[1] Beijing Union Univ, Coll Intellectualized City, Beijing, Peoples R China

[2] Beijing Union Univ, Coll Robot, Beijing, Peoples R China

来源：

2018 14TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2018年

关键词：

component; Feature; Word Vector; styling; Model Integration;

D O I：

10.1109/CIS2018.2018.00046

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

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.

引用

页码：179 / 182

页数：4

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