计算机工程与应用2024，Vol.60Issue(13)：81-91,11.DOI:10.3778/j.issn.1002-8331.2310-0218
约束传播自适应半监督非负矩阵分解聚类算法
Constrained Propagation Self-Adaptived Semi-Supervised Non-Negative Matrix Factorization Clustering Algorithm
摘要
Abstract
Symmetric non-negative matrix factorization(NMF)can naturally capture the embedded clustering structure in the graph representation.It is an important method for linear and nonlinear data clustering applications.However,it is sen-sitive to the initialization of variables,and the quality of the initialization matrix greatly affects the clustering perfor-mance.In semi-supervised clustering,it faces the challenge of learning a more discriminative representation from limited labeled data.This paper introduces a constrained propagation self-adaptive self-supervised non-negative matrix factoriza-tion clustering algorithm(CPS3NMF)to solve the above problems.The algorithm propagates finite constraints to uncon-strained data points,constructing a similarity matrix imbued with constraint information.The resultant similarity matrix serves the role of a non-negative symmetric matrix decomposition in SNMF and functions as graph regularization for the assignment matrix,fully utilizing the limited constraint information to preserve the geometrical structure of data space.Concurrently,leveraging the sensitivity of initial features in SNMF,the algorithm employs adaptively learned weights to rank the quality of multiple initial matrices.By integrating results from multiple clustering attempts,it progressively enhances the performance of semi-supervised clustering.Experiments on 6 public datasets show that the proposed CPS3NMF algo-rithm outperforms other state-of-the-art algorithms,proving its effectiveness in semi-supervised clustering.关键词
对称非负矩阵分解/半监督学习/约束传播/聚类Key words
symmetric non-negative matrix factorization/semi-supervised learning/constraint propagation/clustering分类
信息技术与安全科学引用本文复制引用
朱拓基,林浩申,赵伟豪,王靖,杨晓君..约束传播自适应半监督非负矩阵分解聚类算法[J].计算机工程与应用,2024,60(13):81-91,11.基金项目
广东省自然科学基金面上项目(2021A1515011141) （2021A1515011141）
国家部委基金 （）
国家自然科学基金青年项目(61904041). （61904041）
