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» MapReduce: Simplified Data Processing on Large Clusters
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CLOUDCOM
2010
Springer
13 years 4 months ago
Scheduling Hadoop Jobs to Meet Deadlines
User constraints such as deadlines are important requirements that are not considered by existing cloud-based data processing environments such as Hadoop. In the current implementa...
Kamal Kc, Kemafor Anyanwu
HIS
2004
13 years 9 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
MLDM
2005
Springer
14 years 1 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
SIGMOD
2012
ACM
288views Database» more  SIGMOD 2012»
11 years 10 months ago
Exploiting MapReduce-based similarity joins
Cloud enabled systems have become a crucial component to efficiently process and analyze massive amounts of data. One of the key data processing and analysis operations is the Sim...
Yasin N. Silva, Jason M. Reed
AAAI
2008
13 years 10 months ago
Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Jiayu Zhou, Youfang Lin, Xi Wang