By Topic

Aggregating constraint satisfaction degrees expressed by possibilistic truth values

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
$33 $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)
G. De Tre ; Dept. of Telecommun. & Inf. Process., Gent Univ., Belgium ; B. De Baets

In information systems, one often has to deal with constraints in order to compel the semantics and integrity of the stored information or to express some querying criteria. Hereby, different constraints can be of different importance. A method to aggregate the information about the satisfaction of a finite number of constraints for a given data instance is presented. Central to the proposed method is the use of extended possibilistic truth values (to express the degree of satisfaction of a constraint) and the use of residual implicators and residual coimplicators (to model the impact and relevance of a constraint). The proposed method can be applied to any constraint-based system. A database application is discussed and illustrated.

Published in:

IEEE Transactions on Fuzzy Systems  (Volume:11 ,  Issue: 3 )