A joining implication is a restricted form of an implication where it is explicitly specified which attributesmay occur in the premise and in the conclusion, respectively. A technique for sound and complete axiomatization of joining implications valid in a given formal context is provided. In particular, a canonical base for the joining implications valid in a given formal context is proposed, which enjoys the property of being of minimal cardinality among all such bases. Background knowledge in form of a set of valid joining implications can be incorporated. Furthermore, an application to inductive learning in a Horn description logic is proposed, that is, a procedure for sound and complete axiomatization of Horn-M concept inclusions from ...
Implication is a logical connective corresponding to the rule of causality "if ... then ...". Implic...
International audienceThe notion of dependencies between "attributes" arises in many areas such as r...
This paper aims to be a friendly introduction to formal learning theory. I introduce key concepts at...
A joining implication is a restricted form of an implication where it is explicitly specified which ...
In this paper, we demonstrate how different forms of background knowledge can be integrated with an ...
In this paper, we demonstrate how different forms of background knowledge can be integrated with an ...
URL des Cahiers :http://mse-univ-paris1.fr/MSEFramCahier2005.htmCahiers de la Maison des Sciences Ec...
We characterize two fragments of Horn Description Logics and we define two specialized reasoning alg...
In the area of inductive learning, generalization is a main operation, and the usual de nition of in...
The design of the logical layer of the Semantic Web, and subsequently of the mark-up language SWRL,...
This paper discusses the generalization of definite Horn programs beyond the ordering of logical imp...
AbstractWe describe carin, a novel family of representation languages, that combine the expressive p...
In symbolic Machine Learning, the incremental setting allows to refine/revise the available model wh...
We design learning algorithms for synthesizing invariants using Horn implication counterexamples (Ho...
Description Logics are currently advancing to become a very prominent paradigm for rep-resenting kno...
Implication is a logical connective corresponding to the rule of causality "if ... then ...". Implic...
International audienceThe notion of dependencies between "attributes" arises in many areas such as r...
This paper aims to be a friendly introduction to formal learning theory. I introduce key concepts at...
A joining implication is a restricted form of an implication where it is explicitly specified which ...
In this paper, we demonstrate how different forms of background knowledge can be integrated with an ...
In this paper, we demonstrate how different forms of background knowledge can be integrated with an ...
URL des Cahiers :http://mse-univ-paris1.fr/MSEFramCahier2005.htmCahiers de la Maison des Sciences Ec...
We characterize two fragments of Horn Description Logics and we define two specialized reasoning alg...
In the area of inductive learning, generalization is a main operation, and the usual de nition of in...
The design of the logical layer of the Semantic Web, and subsequently of the mark-up language SWRL,...
This paper discusses the generalization of definite Horn programs beyond the ordering of logical imp...
AbstractWe describe carin, a novel family of representation languages, that combine the expressive p...
In symbolic Machine Learning, the incremental setting allows to refine/revise the available model wh...
We design learning algorithms for synthesizing invariants using Horn implication counterexamples (Ho...
Description Logics are currently advancing to become a very prominent paradigm for rep-resenting kno...
Implication is a logical connective corresponding to the rule of causality "if ... then ...". Implic...
International audienceThe notion of dependencies between "attributes" arises in many areas such as r...
This paper aims to be a friendly introduction to formal learning theory. I introduce key concepts at...