The privacy protection problem in data mining has received increasingly attention and is a
hot topic of current research. To address the problems of large accuracy loss and instability …

A new density peak clustering (DPC) algorithm with adaptive clustering center based on
differential privacy was proposed to solve the problems of poor adaptability of high …

Featured Application Privacy protection and data mining. Abstract This study aims to
improve the quality of the clustering results of the density peak clustering (DPC) algorithm …

Density peaks clustering is a novel and efficient density-based clustering algorithm.
However, the problem of the sensitive information leakage and the associated security risk …

The differential privacy k-means (DP k-means) clustering algorithm emerged to address the
privacy protection challenges in the field of data mining. However, the algorithm encounters …

How to protect users' private data during network data mining has become a hot issue in the
fields of big data and network information security. Most current researches on differential …

Individual privacy may be compromised during the process of mining for valuable
information, and the potential for data mining is hindered by the need to preserve privacy. It …

Fuzzy C-means clustering algorithm is one of the typical clustering algorithms in data mining
applications. However, due to the sensitive information in the dataset, there is a risk of user …

Data clustering has been applied and developed in all walks of life, which can provide
convenience for enterprise service optimization. However, when the original data to be …

By performing K-Means++ clustering on the samples, the sample data set can obtain a better
initial clustering center, and the generation process of this center is transformed using the …