Paper Info
Title
A rule-based data warehouse model
Abstract
A data warehouse is built by collecting data from external sources. Changes that occur have to be reflected in the data warehouse thanks to schema updating or versioning. However a data warehouse has also to evolve according to users' analysis needs. This evolution is rather driven by knowledge than by data. To take into account these changes, we propose a new Rule-based Data Warehouse (R-DW) model in which rules integrate users' knowledge to dynamically create dimension hierarchies. The R-DW model is composed of a fixed part which is a fact table related to its first level dimensions, and an evolving part which contains the rules. Our model allows analysis context evolution and increases interactions between users and the decision support system.
Year
DOI
Venue
2006
10.1007/11788911_29
BNCOD
Keywords
Field
DocType
decision support system,analysis context evolution,data warehouse,fact table,dimension hierarchy,external source,fixed part,r-dw model,rule-based data warehouse model,increases interaction,analysis need,rule based
Data warehouse,Data modeling,Data mining,Rule-based system,Fact table,Computer science,Decision support system,Expert system,Dimensional modeling,Knowledge base,Database
Conference
Volume
ISSN
ISBN
4042
0302-9743
3-540-35969-9
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Cécile Favre111014.96
Fadila Bentayeb219836.79
Omar Boussaid331246.88