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» A Genetic Algorithm for Clustering on Very Large Data Sets
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ICIP
2010
IEEE
13 years 6 months ago
Sparse shapes prototype modeling using genetic algorithms
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...
JPDC
2007
138views more  JPDC 2007»
13 years 8 months ago
Distributed computation of the knn graph for large high-dimensional point sets
High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) gr...
Erion Plaku, Lydia E. Kavraki
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 8 months ago
Data Stream Clustering: Challenges and Issues
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...
Madjid Khalilian, Norwati Mustapha
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 2 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
CLOUDCOM
2010
Springer
13 years 6 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin