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Follow-Up Question Generation Using Neural Tensor Network-Based Domain Ontology Population in an Interview Coaching System
This study proposes an approach to follow-up question generation based on a populated domain ontology in a conversational interview coaching system. The purpose of this study is to generate the follow-up questions which are more related to the meaning beyond the literal content in the user's answer based on the background knowledge in a populated domain ontology. Firstly, a convolutional neural tensor network (CNTN) was applied for selecting a key sentence from the user answer. Secondly, thedoi:10.21437/interspeech.2019-1300 dblp:conf/interspeech/SuWC19 fatcat:ysz47rhukzdrtmhywxn3ztam34