Handwritten Short Answer Evaluation System (HSAES)

Authors

  • Sijimol P J  Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India
  • Surekha Mariam Varghese  Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Keywords:

OCR, Short Answer, NLP, Machine Learning, Scoring

Abstract

This paper presents the design and implementation of an automated evaluation system for short answers. Handwritten Short Answer Evaluation System (HSAES) is an automated short answer evaluation system that is capable of identifying the texts in answer papers and evaluates marks for each short answer based on previous knowledge acquired by the model. Although many essay evaluation systems are available, short answer grading is still a big problem. In the proposed system, Optical Character Recognition tools are used to extract the handwritten texts. Natural Language Processing is used to extract the keywords from human evaluated sample dataset of handwritten answer papers and answer key. The proposed model evaluates scores based on cosine sentence similarity measures. Each sentence in the evaluated answer paper carries their corresponding mark. The developed model can be used to evaluate the marks of the unscored short answers.

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International Journal of Scientific Research in Science and Technology

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Published

2018-02-28

Issue

Volume 4, Issue 2, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRST

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sijimol P J, Surekha Mariam Varghese, " Handwritten Short Answer Evaluation System (HSAES), International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 2, pp.1514-1518, January-February-2018.