This work presents a cube-based approach for incremental data mining that operates on the data, rather than on the data mining algorithms. The idea was to build a compressed replica of the full-blown database by representing the database by means of multi-dimensional cubes, and then applying the original data mining algorithms on the cube-based data. This way, the storage requirement to accommodate the database is not affected by the new data. Yet, the fact that we used the original data mining algorithms on the cube-based data makes our incremental data mining approach very general as it can be applied to all types of data mining models.

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