成都大学学报（自然科学版）2026，Vol.45Issue(2)：161-165,202,6.DOI:10.3969/j.issn.1004-5422.2026.02.007
基于K-means聚类和关联映射算法的数字画像匹配技术
Digital Portrait Matching Technology Based on K-means Clustering and Association Mapping Algorithm
摘要
Abstract
A digital portrait matching technique based on K-means clustering and association mapping al-gorithm is proposed.The K-means clustering algorithm is applied to formulate the clustering partition strat-egy,and a large number of users' digital portraits are divided iteratively to form multiple portrait subsets.Combining latent factor models and matrix factorization concepts,the study generates corresponding cluster labels for each portrait subset.Using the association mapping algorithm,the paper analyzes the overall as-sociation between all cluster labels and the given digital portrait matching requirements in order to find the optimal portrait matching result.The experimental results show that the accuracy value of the digital por-trait matching results generated by this technology is not less than 0.9,indicating the superiority of the digital portrait matching results.关键词
数字画像/K-means聚类/聚类划分策略/关联映射算法/标签生成/群体分类Key words
digital portrait/K-means clustering/clustering partition strategy/association mapping algo-rithm/label generation/group classification分类
信息技术与安全科学引用本文复制引用
宋杰..基于K-means聚类和关联映射算法的数字画像匹配技术[J].成都大学学报（自然科学版）,2026,45(2):161-165,202,6.基金项目
河南省高等学校重点科研项目(25B520052) （25B520052）
