Fahmy, Aly AGomaa, Wael H2019-12-242019-12-242012-112158-107Xhttps://t.ly/dvRZYAccession Number: WOS:000219140300019Most 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.en-USOctober University for University for Corpus-Based SimiarityString SimilaritySemantic SimilarityShort Answer GradingAutomatic ScoringArticle