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| Comprehending Texts and Answering Questions Based on Hierarchical Interactive Network |
Cheng Yong1( ), Xu Dekuan1, Lv Xueqiang2 |
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.
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Received: 24 May 2018
Published: 16 January 2019
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