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

Domaine:

natural language processingeducation

Type de record:

paper
Créateur:
Al-Nam
Éditeur:
BabValSurKan
Éditeur:
CCSDSpringer International Publishing
Hôte:avatar
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT) International audience 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.

Visit

inria.hal.science

Tags

Questions answering systemDerivativesLexical similarityHamming[INFO]Computer Science [cs]

Licenses

http://creativecommons.org/licenses/by/info:eu-repo/semantics/OpenAccess

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