DocumentCode :
257474
Title :
An Automatic English Composition scoring model based on neural network algorithm
Author :
Ya Zhou ; Taosong Fan ; Guimin Huang
Author_Institution :
Sch. of Comput. Sci. & Eng., Guilin Univ. of Electron. Technol., Guilin, China
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
149
Lastpage :
152
Abstract :
In this paper, an Automatic English Composition scoring (AECS) model based on neural network algorithm is constructed by extracting the lexical feature, syntactic feature and readability features which reflect the content writing quality and determining these features´ weight in composition scoring. The model uses training data to train the neural network and eventually it obtains the neural networks indicating the relationship of these features which can be used to predict the English compositions´ final scores. Through an objective comparison of the scores predicted by AECS and experienced teachers, we know that the AECS model we proposed can well reflect the level of students´ writing.
Keywords :
natural language processing; neural nets; AECS model; automatic English composition scoring model; lexical feature; neural network algorithm; readability features; students writing; syntactic feature; Computational modeling; Feature extraction; Mathematical model; Neural networks; Syntactics; Training; Writing; automatic scoring; natural language processing; neural network; text feature extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Science (ICIS), 2014 IEEE/ACIS 13th International Conference on
Conference_Location :
Taiyuan
Type :
conf
DOI :
10.1109/ICIS.2014.6912123
Filename :
6912123
Link To Document :
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