Business Intelligence

Performance Evaluation of Apriori on Dual Core with Multiple Threads

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Executive Summary

The complexity of handling the scalability problem of huge data can be reduced with parallel processing. The efficiency of parallel processing changes as the number of processors or number of threads change. Parallel processing is more appropriate for the field like data mining as it is the technique of analyzing large quantities of data to extract useful knowledge. Data mining is very much essential to the modern society as more and more data is being collected from various fields. Experiments are conducted to test the run time efficiency of the apriori algorithm on dual core processor by changing the number of threads for different databases at different support counts.

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