Paper Info
Title
Modelling Contextual Meta-Knowledge in Temporal Model Based Diagnosis
Abstract
Applying Model Based Diagnosis (MBD) techniques in medical domains reveals the need to use deep causal knowledge modelling frameworks as well as temporal management techniques to capture the dynamic component of disease evolution (with the latter being very important in other domains). Despite the intense research activity in the field of Temporal MBD, there are three issues that have not been analysed in depth: (a) modelling complex interaction of contextual information, (b) evaluation of hypotheses possibility degrees and (c) the structure of explanations. Our aim is to present a general framework for Temporal MBD which approaches these problems and to demonstrate the suitability of the Fuzzy Temporal Constraints Networks formalism (FTCN) for representing the domain temporal dimension.
Year
Venue
Field
2002
FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS
Contextual information,Knowledge modelling,Computer science,Fuzzy logic,Artificial intelligence,Formalism (philosophy),Machine learning
DocType
Volume
ISSN
Conference
77
0922-6389
Citations 
PageRank 
References 
3
0.52
13
Authors
2
Name
Order
Citations
PageRank
José Palma112014.28
Roque Marín219627.43