Name
Abstract | ||
|---|---|---|
Datacubes are specially useful for answering efficiently queries on data warehouses. Nevertheless the amount of generated aggregated data is incomparably more voluminous than the initial data which is itself very large. Recently, research work has addressed the issue of a concise representation of datacubes in order to reduce their size. The approach presented in this paper fits in a similar trend. We propose a concise representation, called Partition Cube, based on the concept of partition and define an algorithm to compute it. Various experiments are performed in order to compare our approach with methods fitting in the same trend. This comparison relates to the efficiency of algorithms computing the representations, the main memory requirements, and the storage space which is necessary. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11827405_40 | DEXA |
Keywords | Field | DocType |
concise representation,similar trend,data warehouse,main memory requirement,partition cube,storage space,lossless reduction,initial data,various experiment,research work,aggregated data | Data warehouse,Data mining,Database query,Computer science,Expert system,Partition (number theory),Data cube,Semantics,Database,Lossless compression,Cube | Conference |
Volume | ISSN | ISBN |
4080 | 0302-9743 | 3-540-37871-5 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alain Casali | 1 | 101 | 12.30 |
| Rosine Cicchetti | 2 | 453 | 175.14 |
| Lotfi Lakhal | 3 | 2245 | 313.14 |
| Noel Novelli | 4 | 127 | 37.10 |