Automatic Generation of Multiple-Choice Fill-in-the-blank Question Using Document Embedding

Information

Title Automatic Generation of Multiple-Choice Fill-in-the-blank Question Using Document Embedding
Authors Junghyuk Park, Hyunsoo Cho, Sang-goo Lee
Year 2018 / 6
Keywords question generation, document embedding, nlp
Publication Type International Conference
Publication International Conference on Artificial Intelligence in Education (AIED 2018), pp. 261--265
Link url

Abstract

Automatic question generation is a challenging task that aims to generate questions from plain texts, and has been widely and actively researched in various fields. Generated questions can be used for educational purposes, largely for mid-terms, final exams, and also for pop quizzes. In this paper, we propose a novel similarity-based multiple choice question generation model without any pre-knowledge or additional dataset.