基于网络平台的个性化知识推荐系统设计  

Design of personalized knowledge recommending system based on the network platform

作　　者：程昌品[1] 邬依林[1] 陈强[1] 姜永生[1] 

机构地区：[1]广东第二师范学院计算机科学系

出　　处：《重庆文理学院学报（社会科学版）》2013年第5期92-96,共5页Journal of Chongqing University of Arts and Sciences（Social Sciences Edition)

基　　金：2012年省高等院校学科建设专项资金资助项目(2012KJCX0079);2013年广东第二师范学院教学研究与改革项目

摘　　要：本文利用学科知识点之间的层次关系图设计知识表示模型,而用户模型则以"用户的认知水平"和"用户兴趣"为中心而构建,在此基础上提出组合过滤推荐算法.该算法保留了内容过滤推荐算法和协同过滤推荐算法的优点,又弥补了两种算法的不足,通过测试评估,验证了组合过滤推荐算法的有效性和准确性.The main problem of the current network teaching platform is the inaccurate personalized knowledge recommendation. Using the hierarchical diagram among the subject knowledge points to design knowledge representation model, the user model was built with ＂user＇ s cognitive level＂ and ＂user＇ s interests＂ as the center. Based on that, the combination filtering recommendation algorithm was put forward, which maintained the advantages of the content filtering recommendation algorithm and collaborative filtering recommen- dation algorithm, and made up the deficiency of the two algorithms. Through test evaluation, the validity and accuracy of the combined filtering recommendation algorithm were verified.

关 键 词：知识表示模型 认知水平 兴趣 用户模型 组合过滤推荐算法 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]