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Automated Essay Scoring using Word2vec and Support Vector Machine

by A. E. E. Elalfi, A. F. Elgamal, N. A. Amasha
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 25
Year of Publication: 2019
Authors: A. E. E. Elalfi, A. F. Elgamal, N. A. Amasha
10.5120/ijca2019919707

A. E. E. Elalfi, A. F. Elgamal, N. A. Amasha . Automated Essay Scoring using Word2vec and Support Vector Machine. International Journal of Computer Applications. 177, 25 ( Dec 2019), 20-29. DOI=10.5120/ijca2019919707

@article{ 10.5120/ijca2019919707,
author = { A. E. E. Elalfi, A. F. Elgamal, N. A. Amasha },
title = { Automated Essay Scoring using Word2vec and Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 25 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 20-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number25/31053-2019919707/ },
doi = { 10.5120/ijca2019919707 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:53.337132+05:30
%A A. E. E. Elalfi
%A A. F. Elgamal
%A N. A. Amasha
%T Automated Essay Scoring using Word2vec and Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 25
%P 20-29
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Essay scoring is one of the most important tools for evaluating and assessing the level of achievement of educational goals. It aims to innovate performance, arrange, integrate ideas, and connect them by using the vocabulary of the particular subjects. Human essay scoring consumes a lot of time and effort, this leads to mistakes. Automated Essay Scoring (AES) solve to great extent problems. A new approach for AES is presented. It is based on Natural Language Processing (NLP) which is used to unify linguistic answers, word2vec model which converts words into features and synonyms in semantic space, Support Vector Machine(SVM) is used to classify students answers and estimate score levels. The system stages consist of preprocessing, feature extraction, classification and similarity algorithm. The results of proposed method reaches high precision (94%) relative to human resident scores.

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Index Terms

Computer Science
Information Sciences

Keywords

Automated Essay Scoring Word2vec Support Vector Machine Natural Language Processing

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