文章基本信息

标题：Which is the Effective Way forGaokao: Information Retrieval or Neural Networks?
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作者：Shangmin Guo ; Xiangrong Zeng ; Shizhu He 等
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2017
卷号：2017
页码：111-120
语种：English
出版社：ACL Anthology
摘要：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.