面向知识推荐服务的选课决策  

Decision Making of Course Selection Oriented by Knowledge Recommendation Service

作　　者：张维国[1] ZHANG Wei-guo(Nanjing Institute of Tourism & Hospitality,Nanjing 211100,China)

机构地区：[1]南京旅游职业学院

出　　处：《计算机科学》2019年第B06期507-510,共4页Computer Science

基　　金：2015年度江苏省高等教育教改立项研究课题(2015JSJG375);全国旅游职业教育教学指导委员会2015年科研项目立项课题(LZW201505);南京旅游职业学院科研课题(2016YKT18)资助

摘　　要：面对Internet的快速发展以及Web上的海量信息资源,用户如何快速并准确地定位到需要的信息成为了一个亟待解决的问题,面向知识推荐服务的选课决策由此产生。面向知识推荐服务的选课是基于个性化推荐研究的核心问题,其以关联规则Apriori算法的理论为基础,运用协同过滤推荐算法,对Apriori算法进行改进,结合学生的专业、兴趣爱好、学习成绩,构建了选课推荐系统模型和基于该模型的个性化推荐算法分析,通过对学生成绩数据库中的数据进行挖掘,指导学生选择更适合自身情况的课程,为学生高效的学习、个性的发展提供帮助。Facing the rapid development of the Internet and the massive information resources on the Web,it is urgent to enable users to quickly find the information they want,hence the course selection oriented to knowledge recommendation service is generated.Course selection oriented to knowledge recommendation service is the core issue in the research of personalized recommendation,Based on the theory of the Apriori algorithm of association rules,this method makes use of the traditional collaborative filtering recommendation algorithm to improve Apriori algorithm.Combined with students’majors,hobbies and academic records,constructs the model of course recommendation system as well as the personalized recommendation algorithm analysis based on this model.Through data mining in the students’academic record database,it guides students to choose more suitable courses and helps them to learn efficiently and develop with personal characteristics.

关 键 词：知识推荐 数据挖掘 关联规则 推荐服务 推荐引擎 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]