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Automated scoring for short answering subjective test in Thai’s language
Author(s): Khantharat Anekboon
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Paper Abstract

Natural language processing is widely used in the real life. Natural language understanding is an important part of it to make a machine understands a language. This paper proposes an automated scoring system for a short answering subjective test in Thai’s language. A finite state machine and word2vec are used to create a scoring machine. Many challenge issues to be solved such as problems of Thai’s language, problems of a small number of words appeared in an answer, and problems about flexible of grading. The proposed method able to create an automated scoring machine after there is an exam question. With the proposed technique, there is no need to wait student’s answers for creating a model as many previous works. The experimental result shows that the proposed method gives a score nearly scoring by humans.

Paper Details

Date Published: 29 October 2018
PDF: 6 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108361J (29 October 2018); doi: 10.1117/12.2511679
Show Author Affiliations
Khantharat Anekboon, King Mongkut's Univ. of Technology North Bangkok (Thailand)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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