2018 · 19 citations · 14 references
ComputingComputer ScienceComputational LinguisticsMachine LearningNatural Language ProcessingLanguage ModelsNatural Language GenerationNatural Language Processing In EducationNatural Language UnderstandingQuestion AnsweringText GenerationEmpirical EvaluationFill-in-the-blank ItemsNeural Question AnsweringQuestion Answering SystemsQuestion Generation
In this paper we formalize the problem automatic fill-in-the-blank question generation using two standard NLP machine learning schemes, proposing concrete deep learning models for each. We present an empirical study based on data obtained from a language learning platform showing that both of our proposed settings offer promising results.
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