http://www.cnr.it/ontology/cnr/individuo/prodotto/ID75356
Joint Queries Estimation from Aggregate OLAP Databases (Contributo in atti di convegno)
- Type
- Label
- Joint Queries Estimation from Aggregate OLAP Databases (Contributo in atti di convegno) (literal)
- Anno
- 2002-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/SSDM.2002.1029728 (literal)
- Alternative label
Pourabbas, E.; Shoshani, A. (2002)
Joint Queries Estimation from Aggregate OLAP Databases
in 14th IEEE International Conference on Scientific and Statistical Database Management-SSDBM 2002, Edinburgh, Scotland, July 24-26, 2002
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Pourabbas, E.; Shoshani, A. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- pp.241,
editore: IEEE Computer Society Press (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- IASI-Istituto di Analisi dei Sistemi ed Informatica \"Antonio Ruberti\" (literal)
- Titolo
- Joint Queries Estimation from Aggregate OLAP Databases (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Abstract
- Given an OLAP query expressed over a collection of sourceOLAP databases, we study the problem of computing the result OLAP target database when the underlying detail data of the source databases are not available. The problem arises when the source databases do not have the same category attributes, and it is not possible to derive the result from a single database. The method we use is the linear indirect estimator. We consider two obvious methods for computing such a target database, called the Full-cross-product (F) and the Pre-aggregation (P) methods. As for the accuracy and computational performance of these methods, while the method F provides the most accurate estimate possible, it is more expressive computationally than P. Our contribution is in proposing a third new method, called the Shortcut method (S), which is less expensive than F, but is as accurate. (literal)
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