计算机应用与软件2024，Vol.41Issue(8)：326-333,397,9.DOI:10.3969/j.issn.1000-386x.2024.08.047
基于无向加权图上信号采样重构的推荐系统预测
PREDICTION OF RECOMMENDER SYSTEM BASED ON SIGNAL SAMPLING RECONSTRUCTION ON UNDIRECTED WEIGHTED GRAPH
摘要
Abstract
In order to effectively capture the potential structure of data and reduce the amount of computation,a recommender system prediction algorithm based on signal sampling reconstruction on undirected weighted graph is proposed.In order to utilize the information carried by unmarked items,users or items and their relationships were modeled as a weighted undirected graph.In order to reconstruct the sampled signal,the problem was approximately modeled as a quadratic unconditional optimization problem in reproducing kernel Hilbert space.In order to reduce the computational complexity,an approximate solution strategy was introduced.The experimental results on two open public databases show that the model significantly improves the prediction accuracy and greatly reduces the computational complexity.关键词
推荐系统/采样重构/希尔伯特空间/加权无向图Key words
Recommender system/Sampling reconstruction/Hilbert space/Weighted undirected graph分类
信息技术与安全科学引用本文复制引用
刘爱民,李茂..基于无向加权图上信号采样重构的推荐系统预测[J].计算机应用与软件,2024,41(8):326-333,397,9.基金项目
湖南省自然科学基金项目(2015JJ2027). （2015JJ2027）
