- Alternative title
-
Effizientes Clustering von großen Datenströmen
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
In: Aachen : Apprimus-Verl., 2015
Aachen, Techn. Hochsch., Dissertation, 2015
- Bibliographic citation
-
Ergebnisse aus der Informatik ; 4
- Keyword
-
Big Data
Data Mining
Cluster-Analyse
Datenstrom
Hochdimensionale Daten
Unterraum
Dichtebasiertes Clusterverfahren
Sensorsystem
Energieeffizienz
- Event
-
Veröffentlichung
- (where)
-
Aachen
- (who)
-
Universitätsbibliothek der RWTH Aachen
- (when)
-
2015
- Creator
- Contributor
-
Seidl, Thomas
Gaber, Mohamed Medhat
Kowalewski, Stefan
- URN
-
urn:nbn:de:hbz:82-rwth-2015-027908
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:57 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Hassani, Marwan
- Seidl, Thomas
- Gaber, Mohamed Medhat
- Kowalewski, Stefan
- Universitätsbibliothek der RWTH Aachen
Time of origin
- 2015
Other Objects (12)
Efficient clustering of big data streams
Correlation Clustering in Data Streams
Big data: sublinear algorithms for distributed data streams
Mining big data streams for multiple concepts
S-RASTER: contraction clustering for evolving data streams
DISCOVERING CLUSTERING PATTERNS FROM E-COUNTER DATA STREAMS
Efficient deadline-aware scheduling for the analysis of Big Data streams in public Cloud
Efficient and scalable patients clustering based on medical big data in cloud platform
A clustering algorithm for multivariate data streams with correlated components
Hierarchical clustering for multiple nominal data streams with evolving behaviour
An efficient reversible privacy-preserving data mining technology over data streams
Big data clustering: data preprocessing, variable selection, and dimension reduction
Efficient clustering of big data streams
Correlation Clustering in Data Streams
Big data: sublinear algorithms for distributed data streams
Mining big data streams for multiple concepts
S-RASTER: contraction clustering for evolving data streams
DISCOVERING CLUSTERING PATTERNS FROM E-COUNTER DATA STREAMS
Efficient deadline-aware scheduling for the analysis of Big Data streams in public Cloud
Efficient and scalable patients clustering based on medical big data in cloud platform
A clustering algorithm for multivariate data streams with correlated components
Hierarchical clustering for multiple nominal data streams with evolving behaviour
An efficient reversible privacy-preserving data mining technology over data streams
Big data clustering: data preprocessing, variable selection, and dimension reduction
Efficient clustering of big data streams
Correlation Clustering in Data Streams
Big data: sublinear algorithms for distributed data streams
Mining big data streams for multiple concepts
S-RASTER: contraction clustering for evolving data streams
DISCOVERING CLUSTERING PATTERNS FROM E-COUNTER DATA STREAMS
Efficient deadline-aware scheduling for the analysis of Big Data streams in public Cloud
Efficient and scalable patients clustering based on medical big data in cloud platform
A clustering algorithm for multivariate data streams with correlated components
Hierarchical clustering for multiple nominal data streams with evolving behaviour
An efficient reversible privacy-preserving data mining technology over data streams