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TDP
2010
166views more  TDP 2010»
15 years 1 months ago
Communication-Efficient Privacy-Preserving Clustering
The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
Geetha Jagannathan, Krishnan Pillaipakkamnatt, Reb...
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
16 years 3 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...
ADBIS
2007
Springer
132views Database» more  ADBIS 2007»
16 years 22 days ago
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Rayner Alfred, Dimitar Kazakov
OTM
2005
Springer
16 years 1 days ago
Web Image Semantic Clustering
This paper provides a novel Web image clustering methodology based on their associated texts. In our approach, the semantics of Web images are firstly represented into vectors of t...
Zhiguo Gong, Leong Hou U, Chan Wa Cheang