- Publications
- Influence
Claim Your Author Page
Ensure your research is discoverable on Semantic Scholar. Claiming your author page allows you to personalize the information displayed and manage publications.
- Elke Achtert, Hans-Peter Kriegel, Arthur Zimek
- SSDBM
- 2008
In order to establish consolidated standards in novel data mining areas, newly proposed algorithms need to be evaluated thoroughly. Many publications compare a new proposition --- if at all --- with… (More)
- Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek
- SIGMOD '13
- 2013
Parallel coordinates are an established technique to visualize high-dimensional data, in particular for data mining purposes. A major challenge is the ordering of axes, as any axis can have at most… (More)
- Elke Achtert, Christian Böhm, Peer Kröger, Peter Kunath, Alexey Pryakhin, Matthias Renz
- SIGMOD '06
- 2006
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the reverse 1-nearest… (More)
Many clustering algorithms are not applicable to high-dimensional feature spaces, because the clusters often exist only in specific subspaces of the original feature space. Those clusters are also… (More)
- Elke Achtert, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Andreas Züfle
- EDBT '09
- 2009
In this paper, we propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem. Compared to the limitations of existing methods for the RkNN search, our approach… (More)
- Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek
- IEEE 28th International Conference on Data…
- 2012
When comparing clustering results, any evaluation metric breaks down the available information to a single number. However, a lot of evaluation metrics are around, that are not always concordant nor… (More)
- Elke Achtert, Christian Böhm, Peer Kröger
- PAKDD
- 2006
Hierarchical clustering algorithms, e.g. Single-Link or OPTICS compute the hierarchical clustering structure of data sets and visualize those structures by means of dendrograms and reachability… (More)
- Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek
- Statistical Analysis and Data Mining
- 2008
In this article, we propose an efficient and effective method for finding arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possible… (More)
- Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek
- SDM
- 2008
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possible arbitrarily… (More)
- Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek
- KDD '06
- 2006
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a common arbitrarily… (More)