Automated essay assessment system using text categorization algorithms

被引：0

作者：

Tahani, H ^{[1
]}

Pino, JA ^{[1
]}

机构：

[1] New Mexico Highlands Univ, Comp & Math Sci Dept, Las Vegas, NM 87701 USA

来源：

MLMTA'03: INTERNATIONAL CONFERENCE ON MACHINE LEARNING; MODELS, TECHNOLOGIES AND APPLICATIONS | 2003年

关键词：

rubric; index terms; subjective evidence; objective evidence; fuzzy integral; weighted average;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automated essay grading has been a topic of research since the early 1960s. This paper introduces the fuzzy integral and the weighted average algorithms for text categorizations and applies these algorithms to an automated essay assessment system that classifies the essays according to their content. This preliminary work is considered to be the prototype for a system that can be used in situations that benefit from ranking documents according to content for small, homogeneous sets. In this paper, holistic assessments were not performed on the essays; however, human-raters were used to score each essay. The result of these algorithms is compared against the vector model algorithm, which is the. preferred classification algorithm in the text categorization field.

引用

页码：102 / 107

页数：6

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