Privacy Preserving Spectral Clustering Over Verticallv Partitioned Data Sets

摘要：

Spectral clustering is one of the most popular modern clustering techniques that often outperforms other clustering techniques. When data owned by different parties are used for analysis, the cooperating parties may need to perform spectral clustering jointly, even if the parties may not be willing to disclose their private data to each other. In this paper we develop privacy preserving spectral clustering protocols over vertically partitioned data sets. Such protocols allow various parties to analyze their data jointly while protecting their privacy.

关键词： spectral clustering privacy preserving

作者: Zhenmin Lin Jerzy W. Jaromczyk

作者单位: Department of Computer Science University of Kentucky Lexington, KY, USA, 40506

会议类型: 国际会议

会议名称: 2011 Eighth International Conference on Fuzzy System and Knowledge Discovery(第八届模糊系统与知识发现国际会议 FSKD 2011)

会议地点: 上海

会议语种:英文

页码: 1254-1259

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）