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SIGMOD
1998
ACM
233views Database» more  SIGMOD 1998»
15 years 10 months ago
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopul...
JFR
2010
119views more  JFR 2010»
15 years 1 months ago
Unsupervised classification of dynamic obstacles in urban environments
This paper presents a solution to the problem of unsupervised classification of dynamic obstacles in urban environments. A track-based model is introduced for the integration of 2...
Roman Katz, Juan Nieto, Eduardo Mario Nebot
TSD
2007
Springer
16 years 12 days ago
On the Relative Hardness of Clustering Corpora
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
David Pinto, Paolo Rosso
SDM
2004
SIAM
253views Data Mining» more  SDM 2004»
15 years 7 months ago
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
GLOBECOM
2006
IEEE
16 years 10 days ago
Distributed Formation of Overlapping Multi-hop Clusters in Wireless Sensor Networks
– Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Most of the published clustering algorithms strive to generate t...
Adel M. Youssef, Mohamed F. Younis, Moustafa Youss...