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Abstract

Abstract structures and generalisations are useful in order to solve common practical problems in A.I. Frames are structures representing stereotyped situations and each frame contains different types of information. A metric space structure is introduced in the set of frames. If A(r) is a reference frame containing information about a reference subject R, and Ac(i) (i=1,...,N) a number N of "candidate frames" C(i), representing subjects similar but not equal to R, a classical problem is the selection of the frame C(j) representing a subject, the most similar to subject R. A procedure which can do this will be a Neural Network Classifier.

Additional information

Authors: CARDENOSA J, FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES);JRC ISPRA ESTAB. (IT);CASTELLANOS J, FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES);JRC ISPRA ESTAB. (IT);GARCIA DEL REAL J, FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES);JRC ISPRA ESTAB. (IT);PANETSOS F FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES), FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES);JRC ISPRA ESTAB. (IT);JRC ISPRA ESTAB. (IT), FACULTAD DE INFORMATICA, UNIVERSIDAD DE MADRID, MADRID (ES);JRC ISPRA ESTAB. (IT)
Bibliographic Reference: PAPER PRESENTED: EURASIP WORKSHOP ON NEURAL NETWORKS, SESIMBRA (PT), FEBRUARY 15-17, 1990 AVAILABLE FROM COMMISSION OF THE EUROPEAN COMMUNITIES, DG XIII-C-3, L-2920 LUXEMBOURG AS PAPER EN 35200 ORA
Availability: Can be ordered online
Record Number: 1989128086900 / Last updated on: 1990-11-01
Category: PUBLICATION
Original language: EN
Available languages: en