A Weighted Slope One Collaborative Filtering Algorithm for Improved User Relevance

Ruizhi Li,Qicheng Liu

2023 International Conference on Artificial Intelligence and Automation Control (AIAC)(2023)

引用 0|浏览0
暂无评分
摘要
Considering the low accuracy of recommendation results of current collaborative filtering algorithms caused by data sparsity, this paper proposes a weighted Slope One collaborative filtering algorithm for improved user relevance (WSOCF-IUR). The proposed algorithm takes into account the influence of the number of different user comments and the number of common rating items on recommendation accuracy. In addition, by incorporating user activity and improving the Pearson correlation coefficient, the algorithm reduces the influence of interfering data on recommendations and improving the overall recommendation accuracy. Experimental results demonstrate that the proposed algorithm achieves better recommendation results than other collaborative filtering recommendation algorithms.
更多
查看译文
关键词
slope one algorithm,data sparsity,collaborative filtering,matrix fill,personalized recommendations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要