An Optimized Method for Access of LOBs in Database Management Systems
p.58
p.58
Uncertain Data Privacy Protection Based on K-Anonymity via Anatomy
p.64
p.64
Embedding Complete Binary Trees into Locally Twisted Cubes
p.70
p.70
An Error-Reduction Method for Temporal Phase Unwrapping Based on Double Three-Step Phase-Shifting and Least-Squares Fitting
p.76
p.76
Research on Clustering Analysis of Big Data
p.82
p.82
Optimization Method of Estimating the Leaf Mass of a Tree
p.88
p.88
Additive-Accelerated Mean Regression Model for Multiple Type Recurrent Events
p.93
p.93
Multiple Variables Time Series Adaptive Prediction Model Based on Grey Theory
p.97
p.97
A Survey on the Siltation Motoring Database for Ultra-Large Reservoir Area
p.104
p.104
Research on Clustering Analysis of Big Data
Abstract:
Data quantity of Big Data was too big to be processed with traditional clustering analysis technologies. Time consuming was long, problem of computability existed with traditional technologies. Having analyzed on k-means clustering algorithm, a new algorithm was proposed. Parallelizing part of k-means was found. The algorithm was improved with the method of redesigning flow with MapReduce framework. Problems mentioned above were solved. Experiments show that new algorithm is feasible and effective.
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Periodical:
Advanced Engineering Forum (Volumes 6-7)
Pages:
82-87
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Online since:
September 2012
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