Abstract

Abstract: - Approximate query processing is often based on analytical methodologies able to provide fast responses to queries. As a counterpart, the approximate answers are affected with a small quantity of error. Nowadays, these techniques are being exploited in data warehousing environments, because the queries devoted to extract information involve high-cardinality relations and, therefore, require a high computational time. Approximate answers are profitably used in the decision making process, where the total precision is not needed. Thus, it is important to provide decision makers with accuracy estimates of the approximate answers; that is, a measure of how much reliable the approximate answer is. Here, a probabilistic model is presented for providing such an accuracy measure when the analytical methodology used for decisional analyses is based on polynomial approximation. This probabilistic model is a Bayesian network able to estimate the relative error of the approximate answers.

Autore Pugliese

• Lefons Ezio , Tangorra Filippo

Tutti gli autori

• LEFONS E.;TANGORRA F.;DI TRIA F.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2010

ISSN

1109-2750

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile