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  • 标题:Short Answer Grading Using String Similarity And Corpus-Based Similarity
  • 本地全文:下载
  • 作者:Wael H Gomaa ; Aly A. Fahmy
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2012
  • 卷号:3
  • 期号:11
  • DOI:10.14569/IJACSA.2012.031119
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Automatic Scoring; Short Answer Grading; Semantic Similarity; String Similarity; Corpus-Based Similarity.
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