【作 者】：
刘忠宝， 宋文爱， 孔祥艳， 李宏艳
【关 键 词 】：
学习资源推荐； 学习者建模； 兴趣图谱； 云计算
【栏 目】：
网络教育
【中文摘要】：
目前，个性化推荐研究不断深入，一些重要的研究成果逐渐在实际应用中取得成效，但仍面临兴趣表达不充分、推荐效率不高等问题。鉴于此，文章综合利用兴趣图谱、本体理论、云计算和信息推荐等技术，对学习者建模与个性化推荐方法展开研究。在深入分析用户行为数据的基础上，利用兴趣图谱对学习者进行建模，研究兴趣图谱的生成、演化与反馈方法，建立云环境下的个性化推荐系统。
【英文摘要】：
At present, with the deepening studies on personalized recommendation, some important research results are successful in the practical application. However, there still exist problems such as inadequate expression of interest and inefficient recommendation. This paper investigates the modeling of learners and the methods of personalized recommendation by using interest mapping, ontology theory, cloud computing and information recommendation. On the basis of in-depth analysis of users' behavior data, this paper makes use of the interest graph to model the learners, and studies the generation, evolution and feedback of the interest graph, establishes a personalized recommendation system in cloud environment.