By Topic

Generalized normal forms for probabilistic relational data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Dey, D. ; Sch. of Bus. Adm., Washington Univ., Seattle, WA, USA ; Sarkar, S.

Several approaches have been proposed for representing uncertain data in a database. These approaches have typically extended the relational model by incorporating probability measures to capture the uncertainty associated with data items. However, previous research has not directly addressed the issue of normalization for reducing data redundancy and data anomalies in probabilistic databases. We examine this issue. To that end, we generalize the concept of functional dependency to stochastic dependency and use that to extend the scope of normal forms to probabilistic databases. Our approach is a consistent extension of the conventional normalization theory and reduces to the latter

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:14 ,  Issue: 3 )