Add to ORKGThis paper shows models of data description that incorporate uncertainty like models of data extension EER, IFO among others. These database modeling tools are compared with the pattern FuzzyEER proposed by us, which is an extension of the EER model in order to manage uncertainty with fuzzy logic in fuzzy databases. Finally, a table shows the components of EER tool with the representation of all the revised models.The past and the future of information systems: 1976-2006 and beyondRed de Universidades con Carreras en Informática (RedUNCI
In practice, we often come across situations where it is necessary to make decisions based on incomp...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
This paper shows models of data description that incorporate uncertainty like models of data extensi...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
Information systems have evolved to the point where it is desirable to capture the vagueness and unc...
This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an ...
Outlining a new research direction in fuzzy set theory applied to data mining, this volume proposes ...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
[EN]Under uncertainty, traditional sets may not be sufficient to represent real-world phenomena, and...
The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and ...
A formal framework for the uniform representation and manipulation of fuzzy and/or uncertain data is...
AbstractKnowledge base systems have a central role in the architecture of intelligent information sy...
A formal framework for the uniform representation and manipulation of fuzzy and/or uncertain data is...
In practice, we often come across situations where it is necessary to make decisions based on incomp...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
This paper shows models of data description that incorporate uncertainty like models of data extensi...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
Information systems have evolved to the point where it is desirable to capture the vagueness and unc...
This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an ...
Outlining a new research direction in fuzzy set theory applied to data mining, this volume proposes ...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
[EN]Under uncertainty, traditional sets may not be sufficient to represent real-world phenomena, and...
The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and ...
A formal framework for the uniform representation and manipulation of fuzzy and/or uncertain data is...
AbstractKnowledge base systems have a central role in the architecture of intelligent information sy...
A formal framework for the uniform representation and manipulation of fuzzy and/or uncertain data is...
In practice, we often come across situations where it is necessary to make decisions based on incomp...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
Combining data from many different sources or from sources that are not entirely trusted brings chal...