Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?

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Authors Shizhu He, Jun Zhao, Xiangrong Zeng, Kang Liu, Shangmin Guo
Journal/Conference Name EACL 2017 4
Paper Category
Paper Abstract As one of the most important test of China, Gaokao is designed to be difficult enough to distinguish the excellent high school students. In this work, we detailed the Gaokao History Multiple Choice Questions(GKHMC) and proposed two different approaches to address them using various resources. One approach is based on entity search technique (IR approach), the other is based on text entailment approach where we specifically employ deep neural networks(NN approach). The result of experiment on our collected real Gaokao questions showed that they are good at different categories of questions, that is IR approach performs much better at entity questions(EQs) while NN approach shows its advantage on sentence questions(SQs). We achieve state-of-the-art performance and show that it{'}s indispensable to apply hybrid method when participating in the real-world tests.
Date of publication 2017
Code Programming Language Java

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