Document worth reading: “Privacy Preserving Utility Mining: A Survey”

In massive info interval, the collected info typically includes rich knowledge and hidden knowledge. Utility-oriented pattern mining and analytics have confirmed a sturdy potential to find these ubiquitous info, which might be collected from various fields and functions, resembling market basket analysis, retail, click-stream analysis, medical analysis, and bioinformatics. However, analysis of these info with delicate personal knowledge raises privateness concerns. To acquire greater trade-off between utility maximizing and privateness preserving, Privacy-Preserving Utility Mining (PPUM) has flip right into a important drawback these days. In this paper, we provide a whole overview of PPUM. We first present the background of utility mining, privacy-preserving info mining and PPUM, then introduce the related preliminaries and downside formulation of PPUM, along with some key evaluation requirements for PPUM. In express, we present and concentrate on the current state-of-the-art PPUM algorithms, along with their advantages and deficiencies intimately. Finally, we highlight and concentrate on some technical challenges and open directions for future evaluation on PPUM. Privacy Preserving Utility Mining: A Survey