Conventional Knowledge-Based Systems (KBS) have no way of detecting or signalling when their knowledge is insufficient to handle a case. Consequently, these systems may produce an uninformed conclusion when presented with a case beyond their current knowledge (brittleness) which results in the KBS giving incorrect conclusions due to insufficient knowledge or ignorance on a specific case. Prudence Analysis (PA) has been shown to be a viable alternative to brittleness in Ripple Down Rules (RDR) knowledge bases. To date, there have been two approaches to Prudence; attribute-based and structural-based prudence. This paper introduces Integrated Prudence Analysis (IPA), a novel Prudence method formed by combining these methods.
History
Volume
10638
Pagination
407-417
Location
Guangzhou, China
Start date
2017-11-14
End date
2017-11-18
ISSN
0302-9743
eISSN
1611-3349
ISBN-13
9783319701387
ISBN-10
3319701398
Language
eng
Publication classification
E Conference publication, E1.1 Full written paper - refereed
Copyright notice
2017, Springer International Publishing AG
Title of proceedings
ICONIP 2017 : Proceedings of the Neural Information Processing International Conference
Event
Neural Information Processing. International Conference (24th : 2017 : Guangzhou, China)