Distributed algorithm for sequential pattern mining on a large sequence dataset
Sequential pattern mining is an active research area because of its diverse applications.
There have been many studies suggesting efficient mining algorithms. However, when the
size of the dataset is large, these algorithms have limitations, such as performance and
scalability. Therefore, parallel mining on a cluster of computers is a necessary issue to study
for the sequential pattern mining problem, as the size of the datasets is increasing. In this
paper, we propose a parallel algorithm to deal this problem, called DSPDBV, using dynamic …
There have been many studies suggesting efficient mining algorithms. However, when the
size of the dataset is large, these algorithms have limitations, such as performance and
scalability. Therefore, parallel mining on a cluster of computers is a necessary issue to study
for the sequential pattern mining problem, as the size of the datasets is increasing. In this
paper, we propose a parallel algorithm to deal this problem, called DSPDBV, using dynamic …
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