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1 Informatyka Teoretyczna i Stosowana

1 2003

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Advanced access to multidimensional data

Białecki A., Wdowiak S.

Informatyka Teoretyczna i Stosowana

2003

R. 3, nr 5

7-18

One of the biggest problems in Data Mining is scalability of developed solutions. It is implied by the following factors: amount of data, splitting data on partitions, curse of dimensionality, many different types of data in the same repository, data neighbourhood and many others. In this paper we propose review of use clustering and space filling in for different areas of data mining. Access to multidimensional data and "what if' queries, typical for OLAP, data warehouses etc. have been discussed. A dedicated GIS Warehouse system as au example of spatial data system is another area of Multidimensional Hierarchical Clustering/ Hierarchy Interleaving. It requires only minor modifications of the typical star schema. Multidimensional data have been presented as a new area for `Z-curves' access methods. Also the idea of `cubegrades' has been reviewed as useful for high level data analysis. Cubegrades are generalised version of association rules.