By Topic

Set differentiation: a method for the automatic generation of filtering algorithms

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

1 Author(s)
Darche, F.D. ; Lab. MASI, Univ. Pierre et Marie Curie, Paris, France

We present a method and its implementation in the GAP system for the automatic generation of filtering algorithms. The evaluation of left-hand sides of rules relies on the matching of condition elements with working memory elements. The filtering is the inference engine phase that performs this matching. Our automatic generation method is based on set differentiation, taking into account both qualitative and quantitative aspects. We present GAP's architecture and show how generic filtering algorithm skeletons are built using set differentials

Published in:

Knowledge-Based Software Engineering Conference, 1996., Proceedings of the 11th

Date of Conference:

25-28 Sep 1996