基于文本挖掘的主观类型电子作业智能辅助评分方法研究  

Research on Intelligent Assistant Evaluation Method for Subjective E-homework Based on Text Mining

作　　者：张大为[1] 王琦菲 ZHANG Dawei;WANG Qifei(College of Computer and Information Technology,Liaoning Normal University,Dalian 116000,China)

机构地区：[1]辽宁师范大学,计算机与信息技术学院,辽宁大连116000

出　　处：《微型电脑应用》2023年第10期5-9,共5页Microcomputer Applications

基　　金：国家自然科学基金课题资助(20200037、20200084);辽宁省科技厅——博士科研启动基金计划项目资助(20210301)。

摘　　要：针对主观类型电子作业人工评阅方式存在的主观性强、准确率低和效率低等问题,提出一种主观类型作业智能辅助评价模型Automatic Scoring Model(ASM),具体包括相似度、主题贴合度、工作量和篇幅结构四项评价指标。采用文本挖掘技术对作业进行量化处理,形成对不同类型作业组织都适用的评价指标。实验表明,ASM模型的评分结果更具有客观合理、准确高效等特点,可以作为主观类型电子作业的辅助评价方法,具有推广应用价值。There are some problems in manual evaluation of subjective E-homework,such as strong subjectivity,low accuracy and low efficiency.This paper proposes an intelligent additive evaluation model for subjective homework automatic scoring model(ASM),which includes similarity index,theme index,workload index,figure index.Text mining technology is used to quantify the homework,which can organize applicable evaluation indexes for different types of homework.Compared with the results of manual scoring,the results of ASM model scoring are more objective,reasonable,accurate and efficient.Therefore,it can be used as an additive evaluation method for subjective E-homework,and has the value of popularization and application.

关 键 词：ASM 文本挖掘 文本主观作业 自动评分 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]