6 Ergebnisse


Günnemann S., Kremer H., Laufkötter C., Seidl T.:
Tracing Evolving Subspace Clusters in Temporal Climate Data
Data Mining and Knowledge Discovery Journal (DMKD), Vol. 24, Nr. 2 S.387-410 (2012)
[Full Text PDF (Springer Open Access)]
Günnemann S., Boden B., Seidl T.:
Finding Density-Based Subspace Clusters in Graphs with Feature Vectors
Data Mining and Knowledge Discovery Journal (DMKD), Vol. 25, Nr. 2 S.243-269 (2012)
[Supplementary Material]


Günnemann S., Färber I., Kremer H., Seidl T.:
CoDA: Interactive Cluster Based Concept Discovery
Proceedings of the VLDB Endowment (PVLDB) 3(2): 1633-1636 (2010) S.1633-1636 (2010) (Demo)
[VLDB 2010]


Müller E., Günnemann S., Assent I., Seidl T.:
Evaluating Clustering in Subspace Projections of High Dimensional Data
Proc. 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, PVLDB Journal, Vol. 2, No. 1, S.1270-1281 (2009) (Experiments and Analyses track, acceptance rate 23.1%)
[VLDB 2009] [Full Text PDF] [Supplementary material]
Schiffer M., Müller E., Seidl T.:
SubRank: Ranking Local Outliers in Projections of High-Dimensional Spaces
Datenbank-Spektrum Vol. 9 Issue 29 S.53-55 (2009) (BTW-Studierendenprogramm)
[DB Spektrum]


Assent I., Krieger R., Müller E., Seidl T.:
VISA: Visual Subspace Clustering Analysis
ACM SIGKDD Explorations Special Issue on Visual Analytics, Vol. 9, Issue 2 S.5-12 (2007)
[SIGKDD Explorations] [Full Text PDF]