Modifications of Uncertain Data: A Bayesian Framework for Belief Revision.

Author List: Dey, Debabrata; Sarkar, Sumit;
Information Systems Research, 2000, Volume 11, Issue 1, Page 1.
The inherent uncertainty pervasive over the real world often forces business decisions to be made using uncertain data. The conventional relational model does not have the ability to handle uncertain data. In recent years, several approaches have been proposed in the literature for representing uncertain data by extending the relational model, primarily using probability theory. The aspect of database modification, however, has not been addressed in prior research. It is clear that any modification of existing probabilistic data, based on new information, amounts to the revision of one's belief about real-world objects. In this paper, we examine the aspect of belief revision and develop a generalized algorithm that can be used for the modification of existing data in a probabilistic relational database. The belief revision scheme is shown to be closed, consistent, and complete.
Keywords: Data Uncertainty; Data Updating; Probabilistic Relational Model
Algorithm:

List of Topics

#6 0.260 data used develop multiple approaches collection based research classes aspect single literature profiles means crowd collected trend accuracy databases accurate
#281 0.185 database language query databases natural data queries relational processing paper using request views access use matching automated semantic based languages
#213 0.182 assimilation beliefs belief confirmation aggregation initial investigate observed robust particular comparative circumstances aggregated tendency factors examine stages uncertainty instead confidence
#37 0.152 intelligence business discovery framework text knowledge new existing visualization based analyzing mining genetic algorithms related techniques large proposed novel artificial
#165 0.128 uncertainty contingency integration environmental theory data fit key using model flexibility perspective environment perspectives high conditions processing examine issue uncertain