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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (12): 23-32    DOI: 10.11925/infotech.2096-3467.2018.0583
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Comprehending Texts and Answering Questions Based on Hierarchical Interactive Network
Yong Cheng1(),Dekuan Xu1,Xueqiang Lv2
1School of Chinese Language and Literature, Ludong University, Yantai 264025, China
2School of Computer Science, Beijing University of Information Technology, Beijing 100192, China
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Abstract  

[Objective] This paper aims to help computer answer questions accurately based on text comprehension. [Methods] First, we proposed a neural network model based on hirrarchical interaction mechanism. We introduced various human thinking mechanism to build this model, which contained hierarchical processing, content filtering and multi-dimensional attention. Then, we ran the proposed model with dataset from Chinese Machine Reading Comprehension (CMRC) 2017. [Results] The precision of the proposed method on test-set was 0.78, which was better than the best result of other published models. [Limitations] There was no further optimization for the potential answers. [Conclusions] The proposed hierarchical interactive network improves machine’s ability to answer questions based on text comprehension.

Key wordsHirarchical Interactive Network      Machine Comprehension      Automatic Question Answering     
Received: 24 May 2018      Published: 16 January 2019

Cite this article:

Yong Cheng,Dekuan Xu,Xueqiang Lv. Comprehending Texts and Answering Questions Based on Hierarchical Interactive Network. Data Analysis and Knowledge Discovery, 2018, 2(12): 23-32.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0583     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I12/23

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