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
The 19th 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.