Automatic Answer Evaluation: NLP Approach

Authors

  • Arun P V Information Technology, College of Science and Technology, Royal University of Bhutan Author
  • Parshu Ram Dungyel Information Technology Department, College of Science and Technology, Royal University of Bhutan Author
  • Karma Wangchuk Information Technology Department, College of Science and Technology, Royal University of Bhutan Author
  • Kesang Wangmo Information Technology Department, College of Science and Technology, Royal University of Bhutan Author
  • Uttar K Rai Information Technology Department, College of Science and Technology, Royal University of Bhutan Author
  • Yeshi Jamtsho Information Technology Department, College of Science and Technology, Royal University of Bhutan Author

Keywords:

Natural Language Processing, Keyword Analysis, Information Extraction, Semantic Matching

Abstract

Automatic assessment of subjective answers requires Natural Language Processing (NLP)-based evaluation and automated assessment. Various techniques used are Ontology, Semantic Similarity Matching, and Statistical Methods. An automatic short answer assessment system based on NLP is attempted in this paper. Various experiments performed on a dataset revealed that the semantic Enhanced NLP (ENLP) method outperformed methods based on simple lexical matching, resulting in up to 85 percent performance with respect to traditional vector-based similarity metrics.

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Published

15-06-2013

Issue

Vol. 1 No. 1 (2013): Zorig Melong|A Technical Journal of Science, Engineering and Technology

Section

Articles

How to Cite

Arun, Dungyel, P. R., Wangchuk, K., Wangmo, K. ., Rai, . U. K. ., & Yeshi Jamtsho, Y. J. (2013). Automatic Answer Evaluation: NLP Approach. Zorig Melong | A Technical Journal of Science, Engineering and Technology, 1(1), 51-56. http://103.133.216.217/index.php/zm/article/view/45

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