@conference {130654,
	title = {A hybrid scheme for Automated Essay Grading based on LVQ and NLP techniques},
	booktitle = {2016 12th International Computer Engineering Conference (ICENCO), },
	year = {2016},
	month = {28-29 Dec},
	address = {Cairo},
	abstract = {<p>This paper presents a hybrid approach to an Automated Essay Grading System (AEGS) that provides automated grading and evaluation of student essays. The proposed system has two complementary components: Writing Features Analysis tools, which rely on natural language processing (NLP) techniques and neural network grading engine, which rely on a set of pre-graded essays to judge the student answer and assign a grade. By this way, students essays could be evaluated with a feedback that would improve their writing skills. The proposed system is evaluated using datasets from computer and information sciences college students{\textquoteright} essays in Mansoura University. These datasets was written as part of mid-term exams in introduction to information systems course and Systems analysis and design course. The obtained results shows an agreement with teachers{\textquoteright} grades in between 70\% and nearly 90\% with teachers{\textquoteright} grades. This indicates that the proposed might be useful as a tool for automatic assessment of students{\textquoteright} essays, thus leading to a considerable reduction in essay grading costs.</p>
},
	url = {http://ieeexplore.ieee.org/document/7856447/},
	author = {Abdulaziz Shehab and Mohamed Elhoseny and Aboul Ella Hassanien}
}
