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Constraint pushing techniques have been proven to be effective in
reducing the search space in the frequent pattern mining task,
and thus in improving efficiency. In this paper, we introduce ExAnte, a pre-processing
data reduction algorithm which reduces dramatically both the
search space and the input dataset in constrained frequent
patterns mining. Experimental results show a reduction of orders
of magnitude, thus enabling a much easier mining task.
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