感知用户的Item-based协同过滤算法

传统的Item-based协同过滤算法中,项目相似度与目标用户是无关的,这可能导致计算出来的项目相似度,对于目标用户来说是不准确的.针对这个缺陷,提出了一种感知用户的Item-based协同过滤算法.该算法综合考虑到目标用户对项目相似度的影响,为不同的用户建立了不同的目标相似度.采用MovieLens数据集作为测试数据,平均绝对误差作为评价指标,实验结果表明,该算法可以有效地提高准确率.

User-aware Item-based Collaborative Filtering Algorithm

In the traditional Item-based collaborative filtering algorithm,the project similarity is not related to the target user,which may lead to the calculated project similarity,which is not accurate for the target user.To solve this problem,aperceptual user's Item-based collaborative filtering algorithm was proposed.The algorithm takes into account the impact of the target user on the similarity of the project,and sets up different target similarity for different users.The MovieLens data set is used as the test data and the average absolute error is taken as the evaluation index.The experimental results showed that the algorithm can improve the accuracy rate effectively.