A knowledge based system for the management ...
Document type :
Article dans une revue scientifique: Article original
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Title :
A knowledge based system for the management of a time stamped uncertain observation set with application on preserving mobility
Author(s) :
Delcroix, V. [Auteur]
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Grislin-Le Strugeon, E. [Auteur]
Puisieux, Francois [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 [LAMIH]
Grislin-Le Strugeon, E. [Auteur]
Puisieux, Francois [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Journal title :
International Journal of Approximate Reasoning
Abbreviated title :
Int. J. Approx. Reasoning
Volume number :
134
Pages :
p. 53-71
Publication date :
2021-07
ISSN :
0888-613X
English keyword(s) :
Information aging
Uncertain information
Information quality
Probabilistic graphical model
Knowledge based system
Reasoning with uncertainty
Uncertain information
Information quality
Probabilistic graphical model
Knowledge based system
Reasoning with uncertainty
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
The aim of this study is to maintain up-to-date information about the current state of elderly people that are medically followed for risks of fall. Our proposal consists of an individual information database management ...
Show more >The aim of this study is to maintain up-to-date information about the current state of elderly people that are medically followed for risks of fall. Our proposal consists of an individual information database management system that can provide information on-demand on various variables. Such a system has to deal with several sources of uncertainty: lack of information, evolving information and reliability of the information sources. We consider that the features of the person may evolve with time causing uncertainty due to obsolete information. Our context includes new information received bit by bit, with no possibility to collect all required information at once. This paper establishes a first proposal to manage a set of uncertain observations, in order to reduce erroneous and obsolete information while keeping the benefit of previously collected information. We propose an architecture of the system based on a probabilistic knowledge model about the characteristics of interest, a set of decay functions that help to evaluate the confidence degree in previous observations, and a reasoning module to manage new observations, maintain the compatibility and the quality of the observation set. We detail the algorithms of the reasoning module, and the algorithm to update the confidence degree of the observations.Show less >
Show more >The aim of this study is to maintain up-to-date information about the current state of elderly people that are medically followed for risks of fall. Our proposal consists of an individual information database management system that can provide information on-demand on various variables. Such a system has to deal with several sources of uncertainty: lack of information, evolving information and reliability of the information sources. We consider that the features of the person may evolve with time causing uncertainty due to obsolete information. Our context includes new information received bit by bit, with no possibility to collect all required information at once. This paper establishes a first proposal to manage a set of uncertain observations, in order to reduce erroneous and obsolete information while keeping the benefit of previously collected information. We propose an architecture of the system based on a probabilistic knowledge model about the characteristics of interest, a set of decay functions that help to evaluate the confidence degree in previous observations, and a reasoning module to manage new observations, maintain the compatibility and the quality of the observation set. We detail the algorithms of the reasoning module, and the algorithm to update the confidence degree of the observations.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CHU Lille
CHU Lille
Submission date :
2023-11-15T09:57:09Z
2024-02-15T12:45:18Z
2024-02-15T12:45:18Z
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