多媒体背景下思政教育资源高效挖掘方法研究  

Research on Efficient Mining Methods of Ideological and Political Education Resources Under Multimedia Background

作　　者：姜姗[1] 赵春霞[1] 朱红磊 JIANG Shan;ZHAO Chunxia;ZHU Honglei(School of Information Technology,Henan University of Traditional Chinese Medicine,Zhengzhou Henan 450046,China)

机构地区：[1]河南中医药大学信息技术学院,河南郑州450046

出　　处：《信息与电脑》2022年第23期238-240,共3页Information & Computer

基　　金：2022年度河南省社会科学界联合会调研课题(项目编号:SKL-2022-887);河南中医药大学2021年教育教学改革研究与实践项目(项目编号:2021JX54);全国高等院校计算机基础教育研究会2022年计算机基础教育教学研究项目(项目编号:2022-AFCEC-307)。

摘　　要：当下思政教育普遍存在教学资料类型单一且落后的问题,为丰富思政教育资源,提出了一种思政教育资源高效挖掘方法。首先,利用主题爬虫技术从网页上收集思政教育资源并组成文本,针对资源文本实施去停用词和分词处理;其次,通过计算文本中每个词汇的词频-逆文档率,提取思政教育资源特征;最后,利用贝叶斯网络构建挖掘模型,实现思政教育资源的分类挖掘。实验结果表明,该方法的相似度较高,均在0.8以上。At present,ideological and political education generally has the problem of single and backward teaching materials.In order to enrich ideological and political education resources,this paper studies an efficient mining method of ideological and political education resources under the multimedia background.Firstly,the theme crawler technology is used to collect ideological and political education resources from the web page and form a text,and the stop words and word segmentation processing are implemented for the resource text.Secondly,the characteristics of ideological and political education resources are extracted by calculating the word frequency inverse document rate of each word in the text.Finally,Bayesian network is used to build a mining model to realize the classified mining of ideological and political education resources.The experimental results show that the similarity of this method reaches the maximum value,which is above 0.8.

关 键 词：思政教育资源 爬虫技术 特征提取 挖掘方法 

分 类 号：G641[文化科学—高等教育学]