Automatic generation of questions based on semantic text analysis
Buldin Ilya, Murov Vadim, Dmitry Sergeevich Silnov · 2020
Recently, scientists have shown great interest in the processing of natural language. This article presents a template-based approach to the automatic generation of test questions that takes note of the semantic structure of the text. The main idea of the work consists in an automated composition of questions for testing from affirmative sentences that make up the text. The generated questions are then selected by the teacher. The results of experiments with text fragments from literary sources on various topics are given. The main problems for further work and successful testing of the software product in the conditions of classrooms of educational institutions are singled out.