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ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
16 years 1 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
WECWIS
2002
IEEE
112views ECommerce» more  WECWIS 2002»
16 years 3 days ago
Separating Business Process from User Interaction Utilizing Process-Aware XSLT Style-Sheets
In the web context, it is difficult to disentangle presentation from process logic, and sometimes even data is not separate from the presentation. Consequently, it becomes to de...
Karl Aberer, Anwitaman Datta, Zoran Despotovic
COOPIS
2004
IEEE
15 years 11 months ago
Comparing Approaches for Semantic Service Description and Matchmaking
Matching descriptions of user requirements against descriptions of service capabilities is crucial for the discovery of appropriate services for a given task. To improve the precis...
Sven Schade, Arnd Sahlmann, Michael Lutz, Florian ...
NOMS
2010
IEEE
136views Communications» more  NOMS 2010»
15 years 5 months ago
Supporting System-wide Similarity Queries for networked system management
Abstract— Today’s networked systems are extensively instrumented for collecting a wealth of monitoring data. In this paper, we propose a framework called System-wide Similarity...
Songyun Duan, Hui Zhang 0002, Guofei Jiang, Xiaoqi...
CIDM
2007
IEEE
16 years 1 months ago
Mining Subspace Correlations
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Rave Harpaz, Robert M. Haralick