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Semantic Attributes Model for Automatic Generation of Multiple Choice Questions
2014
International Journal of Computer Applications
In this research, an automatic multiple choice question generation system for evaluating semantic role labels and named entities is proposed. The selection of the informative sentence and the keyword to be asked about are based on the semantic labels and named entities that exist in the question sentence. The research introduces a novel method for the distractor selection process. Distractors are chosen based on a string similarity measure between sentences in the data set. Eight algorithms of
doi:10.5120/18038-8544
fatcat:dgxvfc37y5avnpn4ajdjs72wle