An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function

吴茜媛; 郑庆华; 刘广东

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An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function

更新时间：2025-12-08

- An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function
- Vol. 42, Issue 12, Pages: 1455-1458(2008)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 December 2008，
  
  Published：2008
- 稿件说明：
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吴茜媛, 郑庆华, 刘广东. An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function[J]. 2008, 42(12): 1455-1458.
DOI：

吴茜媛, 郑庆华, 刘广东. An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function[J]. 2008, 42(12): 1455-1458. DOI：

摘要

针对个性化网络学习中影响学习策略的关键个性特征发现问题

基于粗糙集理论

提出了一种采用分辨函数进行属性约简的算法.应用分辨函数原理

逐次比较论域中的对象

以获取核集和非核集; 利用逻辑运算求取最佳约简

并对约简集合的属性进行影响因子的排序

提取出关键个性特征属性.在西安交通大学英语学习网站平台上的实验结果表明

所提算法得出的学习者关键个性特征维数仅为原始维度的1/4

并可自动发现学习者关键个性特征知识

揭示个性特征和学习策略间的客观关系

精简50%的数据量.

Abstract

To find key characteristic attributes

which have deep influence on learning strategies in network learning

an attribute reduction method is proposed based on rough set theory. The method applies the discernible function principle

constructs core set and nocore set to find the reduction through logic calculation

and sorts the attributes in the reduction set by significance factors to obtain the key characteristic attributes. The method is applied to the network English learning platform of Xi'an Jiaotong University and the result shows the dimensions of key personality characteristics are one-quarter of the original ones. The method can find the knowledge of key attributes and reveal the relation between personality characteristic and learning strategy. Based on the results

the original data volume can be decreased to about 50%.

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references

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Related Institution

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