. The usual model-theoretic semantics for terminological logics are extended to define interpretations for the resulting probabilistic language. It is our main objective to find an adequate modelling of the way the two kinds of probabilistic knowledge are combined in commonsense inferences of probabilistic

We show that the terminological logic ALC comprising Boolean operations on concepts and value restrictions is a notational variant of the propositional modal logic K (m) . To demonstrate the utility of the correspondence, we give two of its immediate by-products. Namely, we axiomatize ALC and give

An attempt is made to integrate three well-known formalisms of knowledge representation: termino-logical logic in the tradition of KL-ONE, the tem-poral logic of Shoham, and Allen’s interval calcu-lus. Drawing on each of these sources, a temporal terminological logic is proposed which combines

: In this paper, we incorporate the notion of rough sets into terminological logics. Terminological logics formalize the classical frame-based knowledge representation systems in AI and can represent and reason about concepts and roles in the objective worlds. In such logics, a concept

d is the representation of the document, n is the representation of the information need and “-+ ” is the conditional connective of the logic in question. In a recent paper we have proposed Terminological Logics (TLs) as suitable logics for modelling IR within the paradigm described above

d is the representation of the document, n is the representation of the information need and “-+ ” is the conditional connective of the logic in question. In a recent paper we have proposed Terminological Logics (TLs) as suitable logics for modelling IR within the paradigm described above

. For such notions, modal logics with possible worlds semantics provides a formally well-founded and wellinvestigated basis. This paper presents a framework for integrating modal operators into terminological knowledge representation languages. These operators can be used both inside of concept expressions

the information expressible in a terminological language can be represented as a semantic network. By contrast, the system of Peirce is very powerful. I show how any information expressed in any terminological language can be transformed and displayed as an existential graph and propose that existential

Terminological Logics are knowledge representation formalisms of enormous applicative interest, as they are specifically oriented to the vast class of application domains that are describable by means of taxonomic organizations of complex objects. A number of results relative to the computational

Information Retrieval (IR) is presented as the task of retrieving the documents that are relevant to a given query. In the context of a Terminological Logic (TL) based approach to IR, this amounts to embodying a notion of relevance in the logical implication relation of the chosen TL. Among