A Review on Natural Language Processing based Automatic Question Generation

Abstract

The advent of the Internet resulted in availability of e-content in huge quantities; this e-content includes information in different domains. This information is being exploited for various reasons and applications. As the formal evaluation and assessment techniques are undergoing transformations, there is also a need for a voluminous Question Bank (QB). The manual creation of questions is a time-consuming and expensive task as it requires domain experts and there is a growing trend towards question bank based question paper generation for assessment. Hence the problem of automatic question generation has attracted attention of the Natural Language Processing (NLP) research community; this problem can be handled by NLP. Automatic generation of high-quality questions is the long-term goal of the Question Generation (QG) research community. The automatic question generation aims to generate all possible questions from the input text or document. This survey article presents the issues, challenges and approaches as well as reviews the reported research work in the context of automatic question generation for different languages at national and international level.