Bayesian networks are tools that were developed by the Artificial Intelligence and Statistic communities for handling uncertainties. This paper explains what they are and to what extent they can be useful in User Modeling. In particular, some applications of Bayesian networks are presented, as well as some clues on how they can be used in User Modeling. Finally, the paper gives an account of the current researches in the field.Cet article a pour but de présenter les réseaux bayésiens, outil issu de l'intelligence artificielle autant que de la statistique, et de montrer leur intérêt pour la modélisation de l 'utilisateur. Il s'attache à présenter différentes applications de cet outil, à proposer des pistes pour son utilisation dans ce domain...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks (BN) are a valid method to analyze causal dependencies with uncertainties and to c...
Abstract—First of all, and to clarify our purpose, it seems important to say that the work we are pr...
Bayesian networks are tools that were developed by the Artificial Intelligence and Statistic communi...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks are powerful tools for representing relations of dependence among variables of a d...
Given the complexity of the domains for which we would like to use computers as reasoning engines, ...
This master's thesis deals with possible applications of Bayesian networks. The theoretical part is ...
Bayesian networks are a popular mechanism for dealing with uncertainty in complex situations. They a...
Bayesian networks are a means to study data. A Bayesian network gives structure to data by creating ...
User modeling is an important component of dialog systems. Most previous approaches are rulebased me...
Bayesian networks have become a widely used method in the modelling of uncertain knowledge. Owing to...
Bayesian networks have established themselves as an indispensable tool in artificial intelligence, ...
The growing area of Data Mining defines a general framework for the induction of models from databas...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks (BN) are a valid method to analyze causal dependencies with uncertainties and to c...
Abstract—First of all, and to clarify our purpose, it seems important to say that the work we are pr...
Bayesian networks are tools that were developed by the Artificial Intelligence and Statistic communi...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks are powerful tools for representing relations of dependence among variables of a d...
Given the complexity of the domains for which we would like to use computers as reasoning engines, ...
This master's thesis deals with possible applications of Bayesian networks. The theoretical part is ...
Bayesian networks are a popular mechanism for dealing with uncertainty in complex situations. They a...
Bayesian networks are a means to study data. A Bayesian network gives structure to data by creating ...
User modeling is an important component of dialog systems. Most previous approaches are rulebased me...
Bayesian networks have become a widely used method in the modelling of uncertain knowledge. Owing to...
Bayesian networks have established themselves as an indispensable tool in artificial intelligence, ...
The growing area of Data Mining defines a general framework for the induction of models from databas...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian networks (BN) are a valid method to analyze causal dependencies with uncertainties and to c...
Abstract—First of all, and to clarify our purpose, it seems important to say that the work we are pr...