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» Cascade Evaluation of Clustering Algorithms
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DMIN
2006
146views Data Mining» more  DMIN 2006»
15 years 1 months ago
A Comparison of Two Document Clustering Approaches for Clustering Medical Documents
Medical data is often presented as free text in the form of medical reports. Such documents contain important information about patients, disease progression and management, but ar...
Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Be...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 7 days ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
CVPR
2006
IEEE
16 years 1 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
15 years 1 months ago
Visually Mining through Cluster Hierarchies
Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aid...
Stefan Brecheisen, Hans-Peter Kriegel, Peer Kr&oum...
DIS
2006
Springer
15 years 3 months ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann