Iceberg-Cube Algorithms for Finding Frequent Combinations of Values: Experiments on Synthetic and Real Databases

L. Findlater and H.J. Hamilton (Canada)


machine learning, data mining,knowledge discovery, data cube, bottom-up computation,top-down computation.


Two straightforward approaches to computing Iceberg Cubes are bottom-up computation and top-down computation. Previously, results based on a single database showed that the bottom-up method is more efficient than the top-down method, even when a pruning capability was added to the top-down method. Here we report on more extensive experiments featuring a variety of synthetic and real databases. Results show that a crossover point occurs at a low minimum support threshold, below which the top-down method is more efficient. The bottom-up method grows increasingly inefficient as the number of results increases.

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