Collaborative Filtering Recommendation Algorithm based on Cluster
Collaborative Filtering Recommendation Algorithm based on Cluster
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DOI：
10.23940/ijpe.18.05.p11.927936
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发表时间：
2018-05
影响因子：
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通讯作者：
Zhiyong Li
中科院分区：
文献类型：
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作者：
Zhiyong Li
传统的协同过滤推荐方法存在数据稀疏、冷启动和效率问题。此外，推荐准确度随着数据量的增加而降低。因此，我们对传统的协同过滤推荐方法进行了改进，在计算用户相似度时增加了用户之间的相同评分，并在集群上运行。由于上述行为，协同过滤推荐方法获得了更好的准确性。实验结果表明，该方法与传统的协同过滤推荐方法相比，具有更高的推荐准确率和推荐效率。
The traditional collaborative filtering recommendation method suffers from sparse datasets, cold starts, and efficiency problems. Furthermore, recommend accuracy decreases with an increase in the amount of data. Therefore, we improved the traditional collaborative filtering recommendation method by increasing the same rating between users when calculating their similarity and running it on a cluster. Because of the above actions, the collaborative filtering recommendation method obtains a better accuracy. Through experiments, we saw that the method we proposed has higher accuracy and efficiency compared to traditional collaborative filtering recommendation methods.