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.
Some of our current research projects are: