Automatic Question Generation with Natural Language Processing and Genetic Algorithm

M. E. Sanap, S. N. Shelke, Saurabh K. Kurhade, Jeevan J. Mahajan, Rahul Kumar


This thesis report describes an intelligent multiple- choice question examination system, named Automatic MCQ Generation, for students . It requires lots of educators efforts  and time since it is tedious and meticulous which can sometimes leads to human mistake .

The purpose of this research is to ease the educators work      in the process of preparation exam questions and giving them more time to concentrate on teaching materials and strengthen their teaching techniques without being burdened with the exam questions preparations.The area of research is multiple choice questions, which are commonly used in educational tests, social surveys, market research and other areas We introduce a rule- based automatic question generation for the task, as well as im- plement statistical sentence selection and various configurations of named entity recognition . Three types of WH-questions (What, Who, and Where) can be produced by our system .

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