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Reseach Article

Automated Essay Evaluation using Chart Parser

by Sampada K.S., Anusha S., N. Vignesh Karthik
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 7
Year of Publication: 2021
Authors: Sampada K.S., Anusha S., N. Vignesh Karthik
10.5120/ijca2021921357

Sampada K.S., Anusha S., N. Vignesh Karthik . Automated Essay Evaluation using Chart Parser. International Journal of Computer Applications. 183, 7 ( Jun 2021), 15-18. DOI=10.5120/ijca2021921357

@article{ 10.5120/ijca2021921357,
author = { Sampada K.S., Anusha S., N. Vignesh Karthik },
title = { Automated Essay Evaluation using Chart Parser },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 7 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 15-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number7/31939-2021921357/ },
doi = { 10.5120/ijca2021921357 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:07.745047+05:30
%A Sampada K.S.
%A Anusha S.
%A N. Vignesh Karthik
%T Automated Essay Evaluation using Chart Parser
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 7
%P 15-18
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Essays help in assessing academic excellence and linking various ideas with the ability to recall. Evaluating essays manually is a tedious and time consuming job. Automated grading shall reduce the evaluation time and with appropriate training, would generate a realistic and accurate score. We aim to develop an automated essay evaluation system by employing a regressor, fed with features like count of misspelt words, sentences, words, characters, nouns, verbs, adverbs, adjectives, and lemmas. Sentences are checked for grammatical correctness using a custom built parser. The regressors are trained on the enlisted features and then measured for the performance. Various regressors like Linear, Logistic and Random Forest have been employed and observed to select a model with the best performance for use.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Natural language Processing Machine Learning NLTK POS-tagger Chart Parser Linear Regression Logistic Regression Random Forest Regression. .