Section: Research Program
Knowledge representation semantics
We work with semantically defined knowledge representation languages (like description logics, conceptual graphs and object-based languages). Their semantics is usually defined within model theory initially developed for logics.
We consider a language as a set of syntactically defined expressions (often inductively defined by applying constructors over other expressions). A representation () is a set of such expressions. It may also be called an ontology. An interpretation function () is inductively defined over the structure of the language to a structure called the domain of interpretation (). This expresses the construction of the “meaning” of an expression in function of its components. A formula is satisfied by an interpretation if it fulfills a condition (in general being interpreted over a particular subset of the domain). A model of a set of expressions is an interpretation satisfying all the expressions. A set of expressions is said consistent if it has at least one model, inconsistent otherwise. An expression () is then a consequence of a set of expressions () if it is satisfied by all of their models (noted ).
The languages dedicated to the semantic web (rdf and owl ) follow that approach. rdf is a knowledge representation language dedicated to the description of resources; owl is designed for expressing ontologies: it describes concepts and relations that can be used within rdf .
A computer must determine if a particular expression (taken as a query, for instance) is the consequence of a set of axioms (a knowledge base). For that purpose, it uses programs, called provers, that can be based on the processing of a set of inference rules, on the construction of models or on procedural programming. These programs are able to deduce theorems (noted ). They are said to be sound if they only find theorems which are indeed consequences and to be complete if they find all the consequences as theorems.