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Most existing
frequent pattern discovery
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algorithms
perform searches in the column/item
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enumeration
space i.e. systematically
testing
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various
combination of columns/items
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For datasets
with 1000-100,000 columns, this
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search space is
enormous
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Instead we adopt
a novel row/sample
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enumeration
algorithm for this purpose.
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CARPENTER
(SIGKDD’03) is the FIRST
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algorithm
which adopt this approach
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