基于支持向量机的英语作文智能分类评分算法研究

R. Xue
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引用次数: 0

摘要

我们研究改变语言使用者写作质量的语言特征,利用综合学习技术提高现有写作自动评价系统的准确性。使用剑桥大学的FCE测试样本,通过向量回归和随机森林算法对对象进行过滤,建立并评价自动评分模式。与现有评价方法相比,提高了综合评价方法的准确性。该方法有效地评估了英语学习者的写作效率,并用于开发大规模计算机测试和在线自主学习系统的写作自助评估系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Intelligent Classification And Grading Algorithm of English Composition Based on Support Vector Machine
We study the language characteristics that change the writing quality of language users to enhance the accuracy of the existing automatic evaluation system for writing using integrated learning technology. The FCE test sample in Cambridge is used, and the object is filtered by vector regression and random forest algorithm to establish and evaluate the automatic scoring mode. Compared with the existing technology, the accuracy of the evaluation using the integrated method is improved. This method effectively evaluates the writing efficiency of English learners and is used to develop a writing self-help evaluation system for large-scale computer tests and online autonomous learning systems.
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