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SIGMOD
2000
ACM
212views Database» more  SIGMOD 2000»
15 years 11 months ago
SQLEM: Fast Clustering in SQL using the EM Algorithm
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...
Carlos Ordonez, Paul Cereghini
DSN
2005
IEEE
16 years 7 days ago
TIBFIT: Trust Index Based Fault Tolerance for Arbitrary Data Faults in Sensor Networks
Since sensor data gathering is the primary functionality of sensor networks, it is important to provide a fault tolerant method for reasoning about sensed events in the face of ar...
Mark D. Krasniewski, Padma Varadharajan, Bryan Rab...
ICML
2006
IEEE
16 years 7 months ago
Combined central and subspace clustering for computer vision applications
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
Le Lu, René Vidal
ACST
2006
15 years 8 months ago
Distributed hierarchical document clustering
This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Debzani Deb, M. Muztaba Fuad, Rafal A. Angryk
PAMI
2008
197views more  PAMI 2008»
15 years 6 months ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...