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» Algorithms for Clustering Data
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ICDE
1999
IEEE
139views Database» more  ICDE 1999»
14 years 9 months ago
Clustering Large Datasets in Arbitrary Metric Spaces
Clustering partitions a collection of objects into groups called clusters, such that similar objects fall into the same group. Similarity between objects is defined by a distance ...
Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehr...
ICASSP
2011
IEEE
12 years 12 months ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
DMIN
2006
146views Data Mining» more  DMIN 2006»
13 years 9 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...
CLUSTER
2008
IEEE
14 years 2 months ago
Enabling lock-free concurrent fine-grain access to massive distributed data: Application to supernovae detection
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
Bogdan Nicolae, Gabriel Antoniu, Luc Bougé
ADBIS
2007
Springer
132views Database» more  ADBIS 2007»
14 years 2 months 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