2009 |
59 | EE | Johannes Aßfalg,
Thomas Bernecker,
Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz:
Periodic Pattern Analysis in Time Series Databases.
DASFAA 2009: 354-368 |
58 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz:
Techniques for Efficiently Searching in Spatial, Temporal, Spatio-temporal, and Multimedia Databases.
DASFAA 2009: 780-783 |
57 | EE | Elke Achtert,
Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz,
Andreas Züfle:
Reverse k-nearest neighbor search in dynamic and general metric databases.
EDBT 2009: 886-897 |
56 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz,
Andreas Züfle,
Alexander Katzdobler:
Incremental Reverse Nearest Neighbor Ranking.
ICDE 2009: 1560-1567 |
55 | EE | Hans-Peter Kriegel,
Peer Kröger,
Erich Schubert,
Arthur Zimek:
Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data.
PAKDD 2009: 831-838 |
54 | EE | Hans-Peter Kriegel,
Peer Kröger,
Arthur Zimek:
Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering.
TKDD 3(1): (2009) |
2008 |
53 | EE | Hans-Peter Kriegel,
Peer Kröger,
Alexey Pryakhin,
Matthias Renz,
Andrew Zherdin:
Approximate Clustering of Time Series Using Compact Model-Based Descriptions.
DASFAA 2008: 364-379 |
52 | EE | Hans-Peter Kriegel,
Peer Kröger,
Alexey Pryakhin,
Matthias Renz:
Analysis of Time Series Using Compact Model-Based Descriptions.
DASFAA 2008: 698-701 |
51 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz:
Continuous proximity monitoring in road networks.
GIS 2008: 12 |
50 | EE | Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Matthias Renz,
Tim Schmidt:
Efficient Query Processing in Large Traffic Networks.
ICDE 2008: 1451-1453 |
49 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
T-Time: Threshold-Based Data Mining on Time Series.
ICDE 2008: 1620-1623 |
48 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Similarity Search in Multimedia Time Series Data Using Amplitude-Level Features.
MMM 2008: 123-133 |
47 | EE | Elke Achtert,
Christian Böhm,
Jörn David,
Peer Kröger,
Arthur Zimek:
Robust Clustering in Arbitrarily Oriented Subspaces.
SDM 2008: 763-774 |
46 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz,
Tim Schmidt:
Hierarchical Graph Embedding for Efficient Query Processing in Very Large Traffic Networks.
SSDBM 2008: 150-167 |
45 | EE | Hans-Peter Kriegel,
Peer Kröger,
Erich Schubert,
Arthur Zimek:
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms.
SSDBM 2008: 418-435 |
44 | EE | Hans-Peter Kriegel,
Peer Kröger,
Arthur Zimek:
Detecting clusters in moderate-to-high dimensional data: subspace clustering, pattern-based clustering, and correlation clustering.
PVLDB 1(2): 1528-1529 (2008) |
2007 |
43 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Efficient Reverse k-Nearest Neighbor Estimation.
BTW 2007: 344-363 |
42 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Ina Müller-Gorman,
Arthur Zimek:
Detection and Visualization of Subspace Cluster Hierarchies.
DASFAA 2007: 152-163 |
41 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Interval-Focused Similarity Search in Time Series Databases.
DASFAA 2007: 586-597 |
40 | EE | Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Matthias Renz,
Tim Schmidt:
Proximity queries in large traffic networks.
GIS 2007: 21 |
39 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Arthur Zimek:
Robust, Complete, and Efficient Correlation Clustering.
SDM 2007 |
38 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Arthur Zimek:
On Exploring Complex Relationships of Correlation Clusters.
SSDBM 2007: 7 |
37 | EE | Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Matthias Renz:
Generalizing the Optimality of Multi-step k -Nearest Neighbor Query Processing.
SSTD 2007: 75-92 |
36 | EE | Hans-Peter Kriegel,
Karsten M. Borgwardt,
Peer Kröger,
Alexey Pryakhin,
Matthias Schubert,
Arthur Zimek:
Future trends in data mining.
Data Min. Knowl. Discov. 15(1): 87-97 (2007) |
35 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Efficient reverse k-nearest neighbor estimation.
Inform., Forsch. Entwickl. 21(3-4): 179-195 (2007) |
2006 |
34 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Semi-Supervised Threshold Queries on Pharmacogenomics Time Sequences.
APBC 2006: 307-316 |
33 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Approximate reverse k-nearest neighbor queries in general metric spaces.
CIKM 2006: 788-789 |
32 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
TQuEST: Threshold Query Execution for Large Sets of Time Series.
EDBT 2006: 1147-1150 |
31 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Similarity Search on Time Series Based on Threshold Queries.
EDBT 2006: 276-294 |
30 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Threshold Similarity Queries in Large Time Series Databases.
ICDE 2006: 149 |
29 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Arthur Zimek:
Deriving quantitative models for correlation clusters.
KDD 2006: 4-13 |
28 | EE | Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin:
Effective similarity search in multimedia databases using multiple representations.
MMM 2006 |
27 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger:
DeLi-Clu: Boosting Robustness, Completeness, Usability, and Efficiency of Hierarchical Clustering by a Closest Pair Ranking.
PAKDD 2006: 119-128 |
26 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Ina Müller-Gorman,
Arthur Zimek:
Finding Hierarchies of Subspace Clusters.
PKDD 2006: 446-453 |
25 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Efficient reverse k-nearest neighbor search in arbitrary metric spaces.
SIGMOD Conference 2006: 515-526 |
24 | EE | Elke Achtert,
Christian Böhm,
Peer Kröger,
Arthur Zimek:
Mining Hierarchies of Correlation Clusters.
SSDBM 2006: 119-128 |
23 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Schubert,
Ziyue Zhu:
Efficient Query Processing in Arbitrary Subspaces Using Vector Approximations.
SSDBM 2006: 184-190 |
22 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Peter Kunath,
Alexey Pryakhin,
Matthias Renz:
Time Series Analysis Using the Concept of Adaptable Threshold Similarity.
SSDBM 2006: 251-260 |
2005 |
21 | EE | Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger:
Online Hierarchical Clustering in a Data Warehouse Environment.
ICDM 2005: 10-17 |
20 | EE | Hans-Peter Kriegel,
Peer Kröger,
Matthias Renz,
Sebastian Wurst:
A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data.
ICDM 2005: 250-257 |
19 | EE | Hans-Peter Kriegel,
Peer Kröger,
Alexey Pryakhin,
Matthias Schubert:
Effective and Efficient Distributed Model-Based Clustering.
ICDM 2005: 258-265 |
18 | EE | Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Petra Linhart:
Selectivity Estimation of High Dimensional Window Queries via Clustering.
SSTD 2005: 1-18 |
17 | EE | Johannes Aßfalg,
Hans-Peter Kriegel,
Peer Kröger,
Marco Pötke:
Accurate and Efficient Similarity Search on 3D Objects Using Point Sampling, Redundancy, and Proportionality.
SSTD 2005: 200-217 |
2004 |
16 | EE | Stefan Brecheisen,
Hans-Peter Kriegel,
Peer Kröger,
Martin Pfeifle,
Maximilian Viermetz,
Marco Pötke:
BOSS: Browsing OPTICS-Plots for Similarity Search.
ICDE 2004: 858 |
15 | EE | Christian Baumgartner,
Claudia Plant,
Karin Kailing,
Hans-Peter Kriegel,
Peer Kröger:
Subspace Selection for Clustering High-Dimensional Data.
ICDM 2004: 11-18 |
14 | EE | Christian Böhm,
Karin Kailing,
Hans-Peter Kriegel,
Peer Kröger:
Density Connected Clustering with Local Subspace Preferences.
ICDM 2004: 27-34 |
13 | EE | Peer Kröger,
Hans-Peter Kriegel,
Karin Kailing:
Density-Connected Subspace Clustering for High-Dimensional Data.
SDM 2004 |
12 | EE | Hans-Peter Kriegel,
Peer Kröger,
Alexey Pryakhin,
Matthias Schubert:
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects.
SDM 2004 |
11 | EE | Stefan Brecheisen,
Hans-Peter Kriegel,
Peer Kröger,
Martin Pfeifle:
Visually Mining through Cluster Hierarchies.
SDM 2004 |
10 | EE | Christian Böhm,
Karin Kailing,
Peer Kröger,
Arthur Zimek:
Computing Clusters of Correlation Connected Objects.
SIGMOD Conference 2004: 455-466 |
9 | | Christian Böhm,
Karin Kailing,
Peer Kröger,
Hans-Peter Kriegel:
Immer größere und komplexere Datenmengen: Herausforderungen für Clustering-Algorithmen.
Datenbank-Spektrum 9: 11-17 (2004) |
2003 |
8 | EE | François Bry,
Peer Kröger:
Bioinformatics Databases: State of the Art and Research Perspectives.
ADBIS 2003: 3 |
7 | EE | Hans-Peter Kriegel,
Peer Kröger,
Zahi Mashael,
Martin Pfeifle,
Marco Pötke,
Thomas Seidl:
Effective Similarity Search on Voxelized CAD Object.
DASFAA 2003: 27- |
6 | EE | Hans-Peter Kriegel,
Peer Kröger,
Irina Gotlibovich:
Incremental OPTICS: Efficient Computation of Updates in a Hierarchical Cluster Ordering.
DaWaK 2003: 224-233 |
5 | EE | Karin Kailing,
Hans-Peter Kriegel,
Peer Kröger,
Stefanie Wanka:
Ranking Interesting Subspaces for Clustering High Dimensional Data.
PKDD 2003: 241-252 |
4 | EE | Hans-Peter Kriegel,
Stefan Brecheisen,
Peer Kröger,
Martin Pfeifle,
Matthias Schubert:
Using Sets of Feature Vectors for Similarity Search on Voxelized CAD Objects.
SIGMOD Conference 2003: 587-598 |
3 | | François Bry,
Peer Kröger:
A Computational Biology Database Digest: Data, Data Analysis, and Data Management.
Distributed and Parallel Databases 13(1): 7-42 (2003) |
2002 |
2 | EE | François Bry,
Peer Kröger:
Datenbanken in der Bioinformatik.
Informatik Spektrum 25(5): 359-362 (2002) |
2001 |
1 | EE | Markus M. Breunig,
Hans-Peter Kriegel,
Peer Kröger,
Jörg Sander:
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering.
SIGMOD Conference 2001: 79-90 |