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This book investigates the challenging research problem of detecting projected outliers that are embedded in high-dimensional data streams. This book is a good reference for outlier detection techniques and approaches in high-dimensional data and data streams. This book also presents an in-depth discussion on a efficient and effective method for detecting projected outliers from high-dimensional data streams through subspace exploration.

Produktbeschreibung
This book investigates the challenging research problem of detecting projected outliers that are embedded in high-dimensional data streams. This book is a good reference for outlier detection techniques and approaches in high-dimensional data and data streams. This book also presents an in-depth discussion on a efficient and effective method for detecting projected outliers from high-dimensional data streams through subspace exploration.
Autorenporträt
Professor Ji Zhang is currently an Associate Professor (Reader) in computing at the University of Southern Queensland, Australia. He is an Australian Endeavour Fellow, Queensland Fellow (Australia) and Izaak Walton Killam Fellow (Canada). His research interests are Knowledge Discovery and Data Mining.