Data Mining and Routing in Traffic Networks

Routing with multiple means of transportation

Modern spatial databases describing traffic networks provide a variety of information about the connections of two locations. For example, a database might store the distance, the speed limit, the altitude difference or the number of traffic lights for each road segment. Thus, a driver might want to consider various criteria at the same time.

Clustering High Dimensional Data

Clusters in subspaces

High-dimensional data is prevalent in many applications and poses several new challenges for clustering algorithms. In this project, we explore the fundamental problems occurring in high dimensional spaces (a.k.a. "curse of dimensionality") in light of clustering and develop new, specialized methods for efficient and effective cluster analysis in high dimensional data.

ELKI: Environment for deveLoping KDD-applications supported by Index-structures

The software system ELKI presents a large collection of data mining algorithms and support of database queries by arbitrary index structures. ELKI also enables to work on arbitrary data types given supporting data classes and distance functions.

Outlier Detection

Data Mining in Bioinformatics

The research group of Hans-Peter Kriegel has a long standing tradition in contributing database support and data mining methods to the application domain of bioinformatics. Among these methods are classification and similarity search in 3D molecular databases, database support for the one-to-many protein docking search, data mining solutions to prediction of protein function, protein structure, and protein subcellular location.

Knowledge Discovery in Large Collection of Complex Objects

High Performance Data Mining

This project deals with performance issues of data mining algorithms. In particular, we explore data structures and new algorithmic concepts to make data mining solutions scalable to very large databases.