Short Answer Grading Using String Similarity And Corpus-Based Similarity

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.

Authors and Affiliations

Wael H Gomaa , Aly A. Fahmy

Keywords

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  • EP ID EP103682
  • DOI 10.14569/IJACSA.2012.031119
  • Views 102
  • Downloads 0

How To Cite

Wael H Gomaa, Aly A. Fahmy (2012). Short Answer Grading Using String Similarity And Corpus-Based Similarity. International Journal of Advanced Computer Science & Applications, 3(11), 115-121. https://europub.co.uk./articles/-A-103682