Description Logic-Based Resource Retrieval

IntroductIon Resource retrieval addresses the problem of finding best matches to a request among available resources, with both the request and the resources described with respect to a shared interpretation of the knowledge domain the resource belongs to. The problem of resource matching and retrieval arises in several scenarios, among them, personnel recruitment and job assignment, dating agencies, but also generic electronic marketplaces, Web services discovery and composition, resource matching in the Grid. All these scenarios share a common purpose: given a request, find among available descriptions those best fulfilling it, or at " worse, " when nothing better exists, those that fulfill at least some of the requirements. Exact, or full, matches are usually rare and the true matchmaking process is aimed at providing one or more " promising " matches to be explored. Non-exact matches should take into account both missing information—details that could be positively assessed in a second phase—and conflicting information—details that could leverage negotiation if the proposed match is worth enough pursuing. Because of its intangibility, it is now a widely shared opinion that knowledge has to be modeled to make unambiguous the interpretation of any information domain. This disambiguation process is usually obtained through an ontology, that is, a specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects (Gruber, 1993). Once a knowledge domain has been mod-eled, and several different resources have been described using such a model, issues that need to be faced for efficient knowledge management are: What, if any, kind of retrieval is possible on these resources? How could we benefit both of the model and formalisms used to build the model, in order to perform a " smart " search of described resources matching a request? The above questions focus on important aspects of knowledge-based retrieval: • formalisms used to model a knowledge domain • retrieval services that fully use the expres-siveness of the formalism to infer new knowledge from the model in order to perform a knowledge-based search Knowledge domain is modeled with a formalism , whose expressiveness is used in the retrieval process to infer not elicited information from the model. In such a context, choosing this formalism strongly affects the complexity, as well as success probability, of the retrieval process. In recent years description logics (DLs) have been investigated by both the academic and industrial world as a …