Publikationen

26 Ergebnisse

2012

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 S.410-420 (2012)
[JDIM ] [Volume 10, Issue 6, December 2012]
Assam R., Hassani M., Seidl T.:
Differential Private Trajectory Obfuscation
Proc. of the 9th International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2012), Beijing, China S.139-151 (2012)
[MOBIQUITOUS 2012]
Tatu A., Maaß F., Färber I., Bertini E., Schreck T., Seidl T., Keim D. A.:
Subspace Search and Visualization to Make Sense of Alternative Clusterings in High-Dimensional Data
Proc. IEEE Symposium on Visual Analytics Science and Technology S.63-72 (2012)
[IEEE-VAST 2012]
Assam R., Seidl T.:
TMC-Pattern: Holistic Trajectory Extraction, Modeling and Mining
Proc. of 1st International Workshop on Analytics for Big Geospatial Data (BigSpatial-2012), held in conjunction with 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2012), Redondo Beach, CA, USA S.71-80 (2012)
[BigSpatial 2012] [ACM SIGSPATIAL GIS 2012]
Zimmer (née Ivanescu) A., Albin T., Abel D., Seidl T.:
Employing the Principal Hessian Direction for Building Hinging Hyperplane Models
Workshop on Optimization Based Techniques for Emerging Data Mining (OEDM 2012) in conjunction with the IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium. S.481-485 (2012) HHmodelsPrincipalHessianDirection.pdf
[ICDM 2012]
Günnemann S., Dao P., Jamali M., Ester M.:
Assessing the Significance of Data Mining Results on Graphs with Feature Vectors
Proc. IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium S.270-279 (2012)
[ICDM 2012]
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)]
Kremer H., Günnemann S., Held A., Seidl T.:
Effective and Robust Mining of Temporal Subspace Clusters
Proc. IEEE International Conference on Data Mining (ICDM), Brussels, Belgium S.369-378 (2012)
[ICDM 2012]
Kranen P., Wels S., Rohlfs T., Raubach S., Seidl T.:
A Tool for Automated Evaluation of Algorithms
Proceedings of The 21st ACM Conference on Information and Knowledge Management (CIKM 2012), Maui, USA S.2692-2694 (2012) (Demo)
Boden B., Günnemann S., Seidl T.:
Tracing Clusters in Evolving Graphs with Node Attributes
Proceedings of The 21st ACM Conference on Information and Knowledge Management (CIKM 2012), Maui, USA  S.2331-2334 (2012) (poster presentation)
Boden B.:
Efficient Combined Clustering of Graph and Attribute Data
PhD Workshop of the 38th International Conference on Very Large Data Bases (VLDB 2012), Istanbul (2012)
[VLDB 2012]
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)
Günnemann S.:
Subspace Clustering for Complex Data
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2012) Tag der mündlichen Prüfung: 15.03.2012
[RWTH Bibliothek] [URN]
Günnemann S., Boden B., Seidl T.:
Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types
Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.280-297 (2012)
[SSDBM 2012]
Zimmer (née Ivanescu) A., Kranen P., Seidl T.:
Hinging Hyperplane Models for Multiple Predicted Variables
Proceedings of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.431-448 (2012) MultivariateHingingHyperplaneModels.pdf
[SSDBM 2012]
Kranen P., Hassani M., Seidl T.:
BT* - An Advanced Algorithm for Anytime Classification
Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.298-315 (2012)
[SSDBM 2012]
Hassani M., Seidl T.:
Resource-Aware Distributed Clustering of Drifting Sensor Data Streams
The 4th International Conference on Networked Digital Technologies (NDT 2012), Dubai, UAE. S.592-607 (2012)
[NDT 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 S.43-50 (2012) DOI: 10.1007/s13222-012-0083-9
[DASP Journal - full text]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2012), Kuala Lumpur, Malaysia (2012)
[PAKDD 2012] [Tutorial Website]
Kremer H., Günnemann S., Held A., Seidl T.:
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases
Proceedings 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Kuala Lumpur, Malaysia S.444-455 (2012)  
[PAKDD 2012] [full text PDF]
Günnemann S., Kremer H., Musiol R., Haag R., Seidl T.:
A Subspace Clustering Extension for the KNIME Data Mining Framework
Proc. IEEE International Conference on Data Mining Workshops (ICDMW), Brussels, Belgium S.886-889 (2012) (Demo)
[ICDM 2012] [Download Page]
Assent I., Kranen P., Baldauf C., Seidl T.:
AnyOut: Anytime Outlier Detection on Streaming Data
The 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012), Busan, South Korea (2012)
[DASFAA 2012]
Zimmer (née Ivanescu) A., Kranen P., Smieschek M., Driessen P., Seidl T.:
PA-Miner: Process Analysis using Retrieval, Modeling, and Prediction
The 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012), Busan, South Korea (2012) (Demo)
[DASFAA 2012]
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B., Read J.:
Stream Data Mining using the MOA Framework
The 17th International Conference on Database Systems for Advanced Applications (DASFAA), Busan, South Korea S.309-313 (2012) (Demo)
[DASFAA 2012]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC, USA (2012)
[ICDE 2012] [Tutorial Website]