Finding non-redundant, statistically significant regions in high dimensional data: a novel approach to projected and subspace clustering

Gabriela Moise, Jörg Sander. Finding non-redundant, statistically significant regions in high dimensional data: a novel approach to projected and subspace clustering. In Ying Li, Bing Liu, Sunita Sarawagi, editors, Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, Nevada, USA, August 24-27, 2008. pages 533-541, ACM, 2008. [doi]

Abstract

Abstract is missing.