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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Short Answer Grading Using String Similarity And Corpus-Based Similarity
Digital Object Identifier (DOI) : 10.14569/IJACSA.2012.031119
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 11, 2012.
Abstract: Most automatic scoring systems use pattern based that requires a lot of hard and tedious work. These systems work in a supervised manner where predefined patterns and scoring rules are generated. This paper presents a different unsupervised approach which deals with students’ answers holistically using text to text similarity. Different String-based and Corpus-based similarity measures were tested separately and then combined to achieve a maximum correlation value of 0.504. The achieved correlation is the best value achieved for unsupervised approach Bag of Words (BOW) when compared to previous work.
Keywords: Automatic Scoring; Short Answer Grading; Semantic Similarity; String Similarity; Corpus-Based Similarity.
Wael H Gomaa and Aly A. Fahmy, “Short Answer Grading Using String Similarity And Corpus-Based Similarity” International Journal of Advanced Computer Science and Applications(IJACSA), 3(11), 2012. http://dx.doi.org/10.14569/IJACSA.2012.031119
@article{Gomaa2012,
title = {Short Answer Grading Using String Similarity And Corpus-Based Similarity},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2012.031119},
url = {http://dx.doi.org/10.14569/IJACSA.2012.031119},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {11},
author = {Wael H Gomaa and Aly A. Fahmy}
}
