Domain specific automatic Chinese multiple-type question generation
Tianlin Zhang, Ying Liu, Pei Quan · 2018
Question Generation is a rising research field of artificial intelligence in education and staff training. It is an effective strategy to conduct knowledge evaluation and performance appraisal. How to generate a variety of good quality questions has been an essential issue. In this paper, we propose an automatic method that generates Chinese multiple-type question by combing diverse knowledge bases and similar language features. Our research is mainly focused on Tradition Chinese Medicine (TCM) domain because it contains many Chinese-based resources and complex relationships. But the method is flexible and can be easily applied to other domains. Experimental results demonstrate that the proposed method obtain a good result.