Paper Info
Title
Representation of Uncertain Knowledge in Probabilistic OLAP Model
Abstract
The probabilistic OLAP model has been presented in this paper. It permits uncertain knowledge to be represented in data warehouse systems. There are two types of uncertainty that can be expressed in this model: imprecise facts and uncertain facts. The former are facts that have occurred but their characteristics are not certain. The latter are facts whose occurrences are uncertain. Typical OLAP algebra operators (set operators, restriction, projection etc.) are included in this model.
Year
DOI
Venue
2008
10.1007/978-3-540-85565-1_12
KES (2)
Keywords
Field
DocType
data warehouse system,probabilistic olap model,uncertain knowledge,projection etc.,imprecise fact,uncertain fact,typical olap algebra operator,probabilistic database,uncertainty,olap,data warehouse,knowledge management
Data warehouse,Data mining,Computer science,Multidimensional model,Operator (computer programming),Probabilistic logic,Online analytical processing,Probabilistic database
Conference
Volume
ISSN
Citations 
5178
0302-9743
0
PageRank 
References 
Authors
0.34
5
1
Name
Order
Citations
PageRank
Maciej Kiewra1466.14