Research on the Automatic Scoring Method of English Essay based on the Improved K-Nearest Neighbor Algorithm

被引：0

作者：

Jiang, Hao ^{[1
]}

Jin, Yaru ^{[1
]}

机构：

[1] Southeast Univ, Sch Comp Sci & Engn, Nanjing 211189, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT AND COMPUTING TECHNOLOGY (ICEMCT-16) | 2016年 / 59卷

关键词：

Automatic Essay Scoring; LSA; Information Gain; K-Nearest Neighbor;

D O I：

暂无

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Compared with the traditional manual marking, automatic English essay scoring can improve the consistency, objectivity, and efficiency of the scoring process. In this essay, the relevant attributes of English composition is extracted, and the improved KNN algorithm is used to score the English essay. The experimental results show that the automatic scoring in which the improved KNN method combines with feature selection has smaller error, compared with manual scoring, and the accuracy of scoring has been improved significantly.

引用

页码：1297 / 1302

页数：6

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