Semantic Attributes Model for Automatic Generation of Multiple Choice Questions

Ibrahim EldesokyFattoh, Amal Elsayed Aboutabl, Mohamed Hassan Haggag
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
more » ... tring similarity measures are used in this research. The system is tested using a set of sentences extracted from the data set for question answering. Experimental results prove that the semantic role labeling and named entity recognition approaches can be used for keyword selection. String similarity measures have been used in generating the distractors in the process of automatic multiple choice questions generation. Combining the similarity measures of some algorithms led to enhancing the results.
doi:10.5120/18038-8544 fatcat:dgxvfc37y5avnpn4ajdjs72wle