摘要
基于数据挖掘技术设计并实现了个性化网络教学系统。该系统添加了数据挖掘模块,模块中采用Clope算法对HTML文档进行聚类分析,找出具有相似特性的学生群体,从而帮助教师进行有针对性的教学;同时,采用Apriori算法,根据学生的访问序列,挖掘出频繁项目集和关联规则模式,从而借助于网络向学生提供个性化教学服务。研究表明:使用数据挖掘技术能在一定程度上提高网络教学系统的个性化推荐服务水平。
On the basis of data mining,the personalized network teaching system is designed and implemented in this article. This system adds a data mining module in which the Clope algorithm is used ,which allows for HTML document clustering analysis. This can identify groups of students with similar characteristics and help teachers carry out targeted teaching. Meanwhile,the improved Apriori algorithm is employed in the module. Based on students＆#39; access sequence, this system digs out frequent itemsets and association rules model ,which provides students with personalized teaching service through the network. The results show that to a certain extent ,the use of data mining techniques can improve personalized recommendation service of network teaching system.
出处
《苏州科技学院学报（自然科学版）》
CAS
2014年第2期75-80,共6页
Journal of Suzhou University of Science and Technology （Natural Science Edition）
关键词
数据挖掘
个性化推荐算法
网络教学系统
个性化推荐服务
data mining
personalized recommendation algorithm
network teaching system
personalized recom-mendation service
作者简介
朱楠（1980一），女，河南新乡人，讲师，硕士，研究方向：软件开发，网页设计。
