Comparison of cosine similarity and k-NN for automated essays scoring
نویسندگان
چکیده
In this paper, a comparison between Cosine Similarity and k-Nearest Neighbors algorithm in Latent Semantic Analysis method to score Arabic essays automatically is presented. It also improves Latent Semantic Analysis by processing the entered text, unifying the form of letters, deleting the formatting, replacing synonyms, stemming and deleting "Stop Words". The results showed that the use of Cosine Similarity with Latent Semantic Analysis led to high results than the use of k-Nearest Neighbors with Latent Semantic Analysis.
منابع مشابه
A Hybrid Method of Syntactic Feature and Latent Semantic Analysis for Automatic Arabic Essay Scoring
Background: The process of automated essays assessments is a challenging task due to the need of comprehensive evaluation in order to validate the answers accurately. The challenge increases when dealing with Arabic language where, morphology, semantic and syntactic are complex. Methodology: There are few research efforts have been proposed for Automatic Essays Scoring (AES) in Arabic. However,...
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