Tutorial 2: Outlier Detection Techniques
This tutorial provides a comprehensive and comparative overview of a
broad range of state-of-the-art algorithms for finding outliers in massive datasets.
It sketches important applications of the introduced methods, and presents a
taxonomy of existing approaches. In addition, relationships between the algorithmic
approaches of each category of the taxonomy are discussed. Last
but not least, at least one algorithm of each category is used for an empirical
evaluation of the different approaches for outlier detection. The intended
audience of this tutorial ranges from novice researchers to advanced experts
as well as practitioners from any application domain where outlier detection
methods are required.
Hans-Peter Kriegel is a full professor for database systems
and data mining in the Department Institute for Informatics
at the Ludwig-Maximilians-Universitat Munchen, Germany
and has served as the department chair or vice chair
over the last years. His research interests are in spatial and
multimedia database systems, particularly in query processing,
performance issues, similarity search, high-dimensional
indexing as well as in knowledge discovery and data mining.
Hans-Peter Kriegel has been chairman and program committee
member in many international database and data mining
conferences. He has published over 200 refereed conference
and journal papers, and he received the SIGMOD Best Paper
Award 1997 and the DASFAA Best Paper Award 2006
together with members of his research team.
Peer Kroger holds a tenured position as Lecturer and Researcher
(Akademischer Rat) at the database systems and
data mining group of Hans-Peter Kriegel at the Ludwig-Maximilians-Universitat Munchen, Germany. He finished his
PhD thesis on clustering moderate-to-high dimensional data
in summer 2004 and his Habilitation in 2009. His research
interests are in data mining and similarity search in high dimensional
multimedia and biomedical data. Peer Kroger published
more than 60 refereed conference and journal papers
and he received the SDM Best Paper Honorable Mention
Award 2008 together with his co-authors.
Arthur Zimek is a postdoc in the database systems and
data mining group of Hans-Peter Kriegel at the Ludwig-Maximilians-Universit at Munchen, Germany. He finished his
PhD thesis on correlation clustering in summer 2008. His research
interests include data mining for high dimensional data
and structured data especially for bioinformatics applications.
Some of his recent publications include contributions to the
tutorialís scope. Arthur Zimek received the SDM Best Paper
Honorable Mention Award 2008 together with his co-authors
and the SIGKDD Doctoral Dissertation Award Runner-Up