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• The SON algorithm lends itself well to a parallel-computing environment. Each of the chunks can be processed in parallel, and the frequent itemsets from each chunk combined to form the candidates.

• We can distribute the candidates to many processors, have each processor count the support for each candidate in a …

SON Algorithm:

• It is an improvement over PCY to count frequent item sets

• The idea is to divide input file into chunks

• Treat each chunk as sample and then find set of frequent item sets in chunks

• We use Ps as a threshold, if each chunk is fraction P of …