Tianci Xia1,2, Yuan Sun1,2,*, Xiaobing Zhao1,2, Wei Song1, Yumiao Guo3
CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 617-628, 2019, DOI:10.32604/cmc.2019.05860
Abstract With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized… More >
Login
Register
