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» From Comparing Clusterings to Combining Clusterings
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SASP
2009
IEEE
170views Hardware» more  SASP 2009»
14 years 3 months ago
Parade: A versatile parallel architecture for accelerating pulse train clustering
— In this paper, we present Parade, a novel and flexible parallel architecture for the deinterleaving of combined pulsetrains. This is a commonly performed task in various areas ...
Amin Ansari, Dan Zhang, Scott A. Mahlke
PAKDD
2009
ACM
225views Data Mining» more  PAKDD 2009»
14 years 6 months ago
Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...
MLDM
2005
Springer
14 years 2 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
DAS
2008
Springer
13 years 11 months ago
A Comparison of Clustering Methods for Word Image Indexing
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...
Simone Marinai, Emanuele Marino, Giovanni Soda
SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
14 years 6 months ago
Context Aware Trace Clustering: Towards Improving Process Mining Results.
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...