%0 Conference Proceedings
%T Evaluating Candidate Answers Based on Derivative Lexical Similarity and Space Padding for the Arabic Language
%+ Babasaheb Bhimrao Ambedkar Bihar University
%A Al-Azani, Samah, Ali
%A Namrata Mahender, C.
%Z Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 4th International Conference on Computational Intelligence in Data Science (ICCIDS)
%C Chennai, India
%Y Vallidevi Krishnamurthy
%Y Suresh Jaganathan
%Y Kanchana Rajaram
%Y Saraswathi Shunmuganathan
%I Springer International Publishing
%3 Computational Intelligence in Data Science
%V AICT-611
%P 102-112
%8 2021-03-18
%D 2021
%R 10.1007/978-3-030-92600-7_10
%K Hamming
%K Lexical similarity
%K Derivatives
%K Questions answering system
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-03772948/document
%2 https://inria.hal.science/hal-03772948/file/512058_1_En_10_Chapter.pdf
%L hal-03772948
%U https://inria.hal.science/hal-03772948
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-ICCIDS
%~ IFIP-AICT-611