Annual Report 2010 - Fachgruppe Informatik an der RWTH Aachen ...

data such that objects within groups are similar while objects in different groups are
dissimilar. In scenarios with many attributes or with noise, clusters are often hidden in
subspaces of the data and do not show up in the full dimensional space. For these
applications, subspace clustering methods aim at detecting clusters in any subspace.
We propose new subspace clustering models which remove redundant information and ensure
the comparability of different clusters to enhance the quality and interpretability of the
clustering results. At the same time the efficiency of the clustering process is guaranteed by
the development of new algorithms. Additionally we focus our research on the evaluation and
visualization of patterns to benefit from human cognitive abilities for the knowledge
generation.
Figure 4: Multiple hidden concepts in subspaces of a high dimensional database
OpenSubspace: An Open Source Framework for Evaluation and Exploration of
Subspace Clustering Algorithms in WEKA
Emmanuel Müller, Stephan Günnemann
Subspace clustering and projected clustering are recent research areas for clustering in high
dimensional spaces. As the field is rather young, there is a lack of comparative studies on the
advantages and disadvantages of the different algorithms. Part of the underlying problem is
the lack of available open source implementations that could be used by researchers to
understand, compare, and extend subspace and projected clustering algorithms. We propose
OpenSubspace, an open source framework that meets these requirements. OpenSubspace
integrates state-of-the-art performance measures and visualization techniques to foster
research in subspace and projected clustering. We currently use this framework both in our
lectures for teaching and in our research projects for experiment evaluation. Our recent
evaluation study published at VLDB 2009 is based on this framework. For further details
please refer to our paper and to the supplementary material to this evaluation study. There,
you can also find further details about possible parameterization of the underlying algorithms
for running experiments. The system is available at
http://dme.rwth-aachen.de/OpenSubspace/.
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