An Adaptive Approach for Subjective Answer Evaluation

EOI: 10.11242/viva-tech.01.02.10

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Vishal Bhonsle, Priya Sapkal, Dipesh Mukadam, Vinit Raut, "An Adaptive Approach for Subjective Answer Evaluation", VIVA-IJRI Volume 1, Issue 2, Article 10, pp. 1-6, 2019. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.


In current academic environment, assignments and home works are very necessary so that students can increase their final grades. This assignments and home works are checked manually by teachers, due to this it consumes lots of time and efforts. Due to manual checking sometimes human error may occur which may affect to student’s grades. Students may misplace their hard copies of assignments because of this they have to rewrite it again. In order to overcome these problems, the proposed system will convert the manual work to digital, in which student will submit their assignments to the system and the system will generate and assign appropriate grades. In the proposed system, by using K Nearest Neighbor Algorithm, it will collect keywords check for the similarity and will generate similarity score. It will also check the relation of the keyword with respect to sentence. To comparing the keywords with synonyms and similar meaning words Semantic Similarity Measure algorithm will be used. After getting the similarity score the grades are assigned accordingly.


data mining, duplication, grading system, KNN, semantics, subjective evaluation.


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