Evaluating Candidate Answers Based on Derivative Lexical Similarity and Space Padding for the Arabic Language - Computational Intelligence in Data Science Access content directly
Conference Papers Year : 2021

Evaluating Candidate Answers Based on Derivative Lexical Similarity and Space Padding for the Arabic Language

Abstract

Character difference represents one of the most common problems that can be occurred when students try to answer questions of fill in the gaps or one-word answer that is needed mostly to one word as the answer. To improve the evolution of the student answer using Hamming distance, we proposed Hamming model tried to solve the drawbacks of the standard Hamming model by applying the stemming approach to achieve derivative lexical similarity and applying the space padding to deal with unequal lengths of the texts.
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hal-03772948 , version 1 (08-09-2022)

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Samah Ali Al-Azani, C. Namrata Mahender. Evaluating Candidate Answers Based on Derivative Lexical Similarity and Space Padding for the Arabic Language. 4th International Conference on Computational Intelligence in Data Science (ICCIDS), Mar 2021, Chennai, India. pp.102-112, ⟨10.1007/978-3-030-92600-7_10⟩. ⟨hal-03772948⟩
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