Abstract. Knowledge-based systems (KBS) are not necessarily based on a well-defined ontologies. In particular it is possible to build very successful KBS for classification problems, but where the classes or conclusions are entered by experts as free-text sentences with little constraint on textual consistency and little systematic organisation of the conclusions. This paper investigates how relations between such ‘classes ’ may be discovered from existing knowledge bases. We have based our approach on KBS built with Ripple Down Rules (RDR). RDR is a knowledge acquisition and knowledge maintenance method which allows KBS to be built very rapidly and simply by correcting errors, but does not require a strong ontology. Our experimental result...
This thesis focuses on reusing domain ontologies and generic problem solvers (PSs) in the developmen...
International audienceKnowledge discovery in large and complex datasets is one main topic addressed ...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
We are currently witnessing a trend toward an architectural separation of a knowledge base (KB) into...
Ripple Down Rules (RDR) were developed in answer to the problem of maintaining medium to large rule-...
Abstract. In this talk, we discuss and illustrate links existing between knowledge discovery in data...
Ripple Down Rules (RDR) is a maturing collection of methodologies for the incremental development an...
The use of ontologies in knowledge engineering arose as a solution to the difficulties associated wi...
International audienceThis chapter deals with the problem of the cooperation of heterogeneous knowle...
Many approaches to knowledge based systems (KBS) development attempt to build complete systems that ...
This article describes the implementation and evaluation of WWW2REL, a domain-independent and patter...
International audienceWe describe RuDiK, an algorithm and a system for mining declarative rules over...
Increasingly, researchers and developers of knowledge based systems (KBS) have been incorporating th...
Ripple Down Rules (RDR) is a knowledge acquisition method for knowledge based systems (KBS) which fa...
Incremental Knowledge Acquisition is an alternative approach to the ”established” knowledg...
This thesis focuses on reusing domain ontologies and generic problem solvers (PSs) in the developmen...
International audienceKnowledge discovery in large and complex datasets is one main topic addressed ...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
We are currently witnessing a trend toward an architectural separation of a knowledge base (KB) into...
Ripple Down Rules (RDR) were developed in answer to the problem of maintaining medium to large rule-...
Abstract. In this talk, we discuss and illustrate links existing between knowledge discovery in data...
Ripple Down Rules (RDR) is a maturing collection of methodologies for the incremental development an...
The use of ontologies in knowledge engineering arose as a solution to the difficulties associated wi...
International audienceThis chapter deals with the problem of the cooperation of heterogeneous knowle...
Many approaches to knowledge based systems (KBS) development attempt to build complete systems that ...
This article describes the implementation and evaluation of WWW2REL, a domain-independent and patter...
International audienceWe describe RuDiK, an algorithm and a system for mining declarative rules over...
Increasingly, researchers and developers of knowledge based systems (KBS) have been incorporating th...
Ripple Down Rules (RDR) is a knowledge acquisition method for knowledge based systems (KBS) which fa...
Incremental Knowledge Acquisition is an alternative approach to the ”established” knowledg...
This thesis focuses on reusing domain ontologies and generic problem solvers (PSs) in the developmen...
International audienceKnowledge discovery in large and complex datasets is one main topic addressed ...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...