DocumentCode
3308720
Title
An Effective Automated Essay Scoring System Using Support Vector Regression
Author
Li, Yali ; Yan, Yonghong
Author_Institution
Key Lab. of Speech Acoust. & Content Understanding, Beijing, China
fYear
2012
fDate
12-14 Jan. 2012
Firstpage
65
Lastpage
68
Abstract
In this paper, we introduce an effective automated essay scoring system. To implement the system, we extract several features, including the surface features such as the number of words in the essay, number of words longer than 5, and complex features such as grammar checking, sentences, whether the essay is off-topic, the similarity to full-score essays. We get the result of 86% precision given the two scores deviation and average deviation of 0.88 compared to human score on real CET4 data.
Keywords
educational administrative data processing; regression analysis; support vector machines; complex features; effective automated essay scoring system; feature extraction; grammar checking; sentences; support vector regression; surface features; Feature extraction; Grammar; Humans; Mutual information; Speech; Vectors; CET4; automated essay scoring;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2012 Fifth International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-1-4673-0470-2
Type
conf
DOI
10.1109/ICICTA.2012.23
Filename
6150237
Link To Document