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Institute for Informatics
Lehrstuhl für Datenbanksysteme und Data Mining
Prof. Dr. Thomas Seidl, Ordinarius
Prof. Dr. Christian Böhm, Extraordinarius
Prof. Dr. Hans-Peter Kriegel (em.)
Prof. Dr. Volker Tresp, Honorarprofessor
Prof. Dr. Peer Kröger (apl.)
Prof. Dr. Matthias Schubert (apl.)

In modern information systems, the sheer amount as well as the complexity of the stored data are increasing at a high rate. This trend is known as Big Data in industry or Data-intensive (Analysis-driven) Science in academia. To search and analyze these large amounts of complex objects, Data Mining and Complex Search, such as similarity search, offer new possibilities to maximize the utilization of available information.

Among other topics, our group is well-known for the development of various
al­go­rithms and access structures for high-dimensional indexing like the R*-tree,
X-Tree or the IQ-Tree. In the area of data mining, the members of our group
contributed va­rious algorithms and methods such as DBSCAN, OPTICS or LOF
which are among the state-of-the-art solutions for clustering and outlier detection.
We also host the Data Science Lab at the LMU München.

Some of our current research projects are:

  • Clustering and Outlier Detection in high-dimensional data
  • Query Processing in Uncertain Databases
  • Efficient Similarity Search and Data Mining in Medical Image Data
  • Database and Search Technologies in Automotive Environments