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An approach for generalising symbolic knowledge

conference contribution
posted on 2008-12-01, 00:00 authored by Richard DazeleyRichard Dazeley, B H Kang
Many researchers and developers of knowledge based systems (KBS) have been incorporating the notion of context. However, they generally treat context as a static entity, neglecting many connectionists' work in learning hidden and dynamic contexts, which aids generalization. This paper presents a method that models hidden context within a symbolic domain achieving a level of generalisation. Results indicate that the method can learn the information that experts have difficulty providing by generalising the captured knowledge. © 2008 Springer Berlin Heidelberg.

History

Volume

5360 LNAI

Pagination

379 - 385

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783540893776

ISBN-10

3540893776

Publication classification

E1.1 Full written paper - refereed

Title of proceedings

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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