摘要
符合学习者特征的学习资源对于提高协作学习效率具有重要的影响。但是传统的学习资源推荐,没有充分考虑学习者、学习资源的特征和高效的推荐算法。针对上述问题,提出了基于协同过滤的学习资源推荐算法,根据学习者学习特征、学习资源特征和学习者对学习资源历史评价信息,采用协同过滤推荐算法,实现学习资源推荐。首先,通过学习者特征和学习资源的评分,寻找相似学习者并计算学习资源预测评分,然后根据该评分值和学习资源与学习者匹配度推荐学习资源,从而为学习者推荐符合自己兴趣爱好最合适的学习资源。实验结果表明该算法在个性化学习资源推荐的准确性上优于传统算法。
The appropriate learning material is very important to improve learners＆#39; learning efficiency in cooperative learning environ-ment. However,traditional recommendation of learning material doesn＆#39;t consider the learner features,learning materials features and rec-ommendation algorithm enough. To solve the problems,propose a personalized learning materials recommendation algorithm based on collaborative filtering,which takes the learners＆#39; learning features,the features of learning materials and the historical assessment informa-tion of learners to learning material into consideration,using the collaborative recommendation algorithm to realize the learning material recommending. First,through the score of learner feature and learning material,search the similar learners and compute the learning mate-rial prediction score. Then,based on predicting ratings and relationship between leaner and learning materials,produce the final recom-mending learning materials. Experimental results show that the proposed algorithm outperforms the other recommendation ones in recom-mending accuracy.
出处
《计算机技术与发展》
2014年第10期63-66,70,共5页
Computer Technology and Development
基金
国家自然科学基金资助项目(31271110)
中央高校基本科研业务费专项资金项目(GK201002028
GK201101001)
关键词
协同过滤算法
学习资源推荐
协作学习
collaborative filtering algorithm
learning materials recommendation
collaborative learning
