This paper propose a parallel Apriori algorithm based on GPU (GPUApriori) for frequent itemsets mining, and designs a storage structure using bit table (BIT) matrix to replace the traditional storage mode. In addition, parallel computing scheme on GPU is discussed. The experimental results show that GPUApriori algorithm can effectively improve the efficiency of frequent itemsets mining
We present a survey of the most important algorithms that have been pro- posed in the context of the...
Frequent Itemset Mining is an important data mining task in real-world applications. Distributed par...
© 2018 This paper investigates the use of GPU (Graphics Processing Unit) in improving the bees swarm...
Part 4: Session 4: Multi-core Computing and GPUInternational audienceFrequent Itemset Mining (FIM) i...
We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-g...
In this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient and hig...
AbstractIn this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient...
Frequent-itemset mining is an important part of data mining. It is a computational and memory intens...
Apriori Algorithms are used on very large data sets with high dimensionality. Therefore parallel com...
Frequent itemset mining (FIM) algorithms extract subsets of items that occurs frequently in a collec...
Abstract—The graphics processing unit (GPU) has evolved into a key part of today’s heterogeneous par...
Frequent itemset mining leads to the discovery of associations and correlations among items in large...
In this paper, we describe GPU-Eclat algorithm, a GPU (General Purpose Graphics Processing Unit) enh...
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining task...
In this paper, we studied the parallelization of K-Means clustering algorithm, proposed a parallel s...
We present a survey of the most important algorithms that have been pro- posed in the context of the...
Frequent Itemset Mining is an important data mining task in real-world applications. Distributed par...
© 2018 This paper investigates the use of GPU (Graphics Processing Unit) in improving the bees swarm...
Part 4: Session 4: Multi-core Computing and GPUInternational audienceFrequent Itemset Mining (FIM) i...
We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-g...
In this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient and hig...
AbstractIn this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient...
Frequent-itemset mining is an important part of data mining. It is a computational and memory intens...
Apriori Algorithms are used on very large data sets with high dimensionality. Therefore parallel com...
Frequent itemset mining (FIM) algorithms extract subsets of items that occurs frequently in a collec...
Abstract—The graphics processing unit (GPU) has evolved into a key part of today’s heterogeneous par...
Frequent itemset mining leads to the discovery of associations and correlations among items in large...
In this paper, we describe GPU-Eclat algorithm, a GPU (General Purpose Graphics Processing Unit) enh...
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining task...
In this paper, we studied the parallelization of K-Means clustering algorithm, proposed a parallel s...
We present a survey of the most important algorithms that have been pro- posed in the context of the...
Frequent Itemset Mining is an important data mining task in real-world applications. Distributed par...
© 2018 This paper investigates the use of GPU (Graphics Processing Unit) in improving the bees swarm...
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