In this paper we give a possible model for handling uncertain information. The concept of fuzzy knowledge-base will be defined as a quadruple of any background knowledge, defined by the proximity of predicates and terms; a deduction mechanism: a fuzzy Datalog program; a connecting algorithm, which connects the background knowledge with the program and a decoding set of the program, which help us to determine the uncertainty level of the results. Evaluation strategies will also be presented
The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Fact...
In this work some possible models for handling uncertain information are presented. These models are...
The Rule Interchange Format (RIF) is a W3C recommendation that allows rules to be exchanged between ...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
The basic question of our study is to present a possible model for handling uncertain information. T...
Abstract. The basic aim of our study is to give a possible model for han-dling uncertain information...
The basic aim of our study is to give a possible model for handling uncertain information. This mode...
The necessity of dealing with uncertain knowledge has arisen from Semantic Web applications in diffe...
We discuss an environment that permits flexible modeling and fuzzy querying of complex data and know...
Fuzzy logic methods permit experts to assess parameters affecting performance of components/systems ...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Purpose Expert systems are computer-based systems that mimic the logical processes of human experts ...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Fact...
In this work some possible models for handling uncertain information are presented. These models are...
The Rule Interchange Format (RIF) is a W3C recommendation that allows rules to be exchanged between ...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
The basic question of our study is to present a possible model for handling uncertain information. T...
Abstract. The basic aim of our study is to give a possible model for han-dling uncertain information...
The basic aim of our study is to give a possible model for handling uncertain information. This mode...
The necessity of dealing with uncertain knowledge has arisen from Semantic Web applications in diffe...
We discuss an environment that permits flexible modeling and fuzzy querying of complex data and know...
Fuzzy logic methods permit experts to assess parameters affecting performance of components/systems ...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguo...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Purpose Expert systems are computer-based systems that mimic the logical processes of human experts ...
Combining data from many different sources or from sources that are not entirely trusted brings chal...
The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Fact...
In this work some possible models for handling uncertain information are presented. These models are...
The Rule Interchange Format (RIF) is a W3C recommendation that allows rules to be exchanged between ...