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ICDAR
2003
IEEE
15 years 11 months ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...
PVLDB
2010
146views more  PVLDB 2010»
15 years 1 months ago
HaLoop: Efficient Iterative Data Processing on Large Clusters
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing pl...
Yingyi Bu, Bill Howe, Magdalena Balazinska, Michae...
DEXA
2009
Springer
175views Database» more  DEXA 2009»
16 years 1 months ago
RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries
Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at different levels of detail with On-Line Analyt...
Fadila Bentayeb, Cécile Favre
BMCBI
2010
144views more  BMCBI 2010»
15 years 6 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
TMC
2008
210views more  TMC 2008»
15 years 5 months ago
Adaptive Cluster-Based Data Collection in Sensor Networks with Direct Sink Access
Recently wireless sensor networks featuring direct sink access have been studied as an efficient architecture to gather and process data for numerous applications. In this paper, w...
Mahdi Lotfinezhad, Ben Liang, Elvino S. Sousa