An Approach for Acquiring Domain Knowledge During the Case Based Reasoning: the System FrakaS-DL
Hioual Ouided, Laskri Mohamed Tayeb
Journal of Data Processing, Vol. 2, No. 2, 2012.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v1n2/4.pdf
Abstract:
As a young discipline at the junction of computer science, artificial intelligence and cognitive sciences, knowl-edge engineering aims at modelling knowledge of a specific domain to operationalise them in a computer system. To this end,it offers theoretical tools, models and empirical methodologies to support Knowledge sharing between the user and thesystem. The work developed here is related to knowledge engineering of a particular type of system: case-based reasoningsystems (CBR) The case-based reasoning (CBR) is to solve a problem by remembering and adapting past cases alreadyresolved. The CBR systems handle various kinds of knowledge: the case, the domain knowledge, knowledge of similarity andadaptation. The cases are collected in a gradual manner when using the system and the case base is enriched incrementally,while other types of knowledge are typically acquired when the system design. In particular the domain knowledge.This paper presents an approach for acquiring domain knowledge-based adaptation system failures. This approach has beenimplemented in a prototype, called FRAKAS, using the description logic.