Publications

10 results

Journal Articles (peer reviewed)

Hassani M., Kim Y., Seungjin Choi, Seidl T.:
Subspace Clustering of Data Streams: New Algorithms and Effective Evaluation Measures
(JIIS) Journal of Intelligent Information Systems (to appear) (2014)
Hassani M., Seidl T.:
Distributed Weighted Clustering of Evolving Sensor Data Streams with Noise
Journal of Digital Information Management (JDIM) Volume 10, No. 6, December 2012 P.410-420 (2012)
[JDIM ] [Volume 10, Issue 6, December 2012]
Kranen P., Assent I., Seidl T.:
An Index-inspired Algorithm for Anytime Classification on Evolving Data Streams
Datenbank-Spektrum (Springer DASP), Volume 12, Issue 1 P.43-50 (2012) DOI: 10.1007/s13222-012-0083-9
[DASP Journal - full text]
Kranen P., Assent I., Baldauf C., Seidl T.:
The ClusTree: Indexing Micro-Clusters for Anytime Stream Mining
Knowledge and Information Systems Journal (Springer KAIS), Volume 29, Issue 2 P.249-272 (2011) DOI 10.1007/s10115-010-0342-8
[KAIS Journal - full text]
Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis P.44-50 (2010)
[www.pascal-network.org/wapa2010] [JMLR Proc. Vol. 11] [pdf]
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) P.1633-1636 (2010) (Demo)
[VLDB 2010]
Kranen P., Seidl T.:
Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
Data Mining and Knowledge Discovery Journal (Springer DMKD), Special Issue on Selected Papers from ECML PKDD 2009, Vol. 19, No. 2, P.245-260 (2009) [DOI 10.1007/s10618-009-0139-0]
[DMKD Journal - full text]
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, P.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 P.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 P.5-12 (2007)
[SIGKDD Explorations] [Full Text PDF]

Conference papers (peer reviewed)

Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis P.44-50 (2010)
[www.pascal-network.org/wapa2010] [JMLR Proc. Vol. 11] [pdf]