Abstract not found

Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery. 1.

Methods for computing the least common subsumer (lcs) are usually restricted to rather inexpressive DLs whereas existing knowledge bases are written in very expressive DLs. In order to allow the user to re-use concepts defined in such terminologies and still support the definition of new concepts by computing the lcs, we extend the notion of the lcs of concept descriptions to the notion of the lcs w.r.t. a background terminology.

Abstract. One of the challenging problems that Web service technology faces is the ability to effectively discover services based on their capabilities. We present an approach to tackle this problem in the context of DAML-S ontologies of services. The proposed approach enables to select the combinations of Web services that best match a given request Q and effectively computes the extra information with respect to Q (e.g., the information required by a service request but not provided by any existing service). We study the reasoning problem associated with such a matching process and propose an algorithm derived from hypergraphs theory.

Approximation is a new inference service in Description Logics first mentioned by Baader, Küsters, and Molitor. Approximating a concept, defined in one Description Logic, means to translate this concept to another concept, defined in a second typically less expressive Description Logic, such that both concepts are as closely related as possible with respect to subsumption. The present paper provides the first in-depth investigation of this inference task. We prove that approximations from the Description Logic ALC to ALE always exist and propose an algorithm computing them. As a measure for the accuracy of the approximation, we introduce a syntax-oriented difference operator, which yields a concept that contains all aspects of the approximated concept that are not present in the approximation. It is also argued that a purely semantical difference operator, as introduced by Teege, is less suited for this purpose. Finally, for the logics under consideration, we propose an algorithm computing the difference.

In this paper, we investigate a first step towards the long-term vision of the Semantic Web by studying the problem of answering queries posed through a mediated ontology to multiple information sources whose content is described as views over the ontology relations. The contributions of this paper are twofold. We first o#er a uniform logical setting which allows us to encompass and to relate the existing work on answering and rewriting queries using views. In particular, we make clearer the connection between the problem of rewriting queries using views and the problem of answering queries using extensions of views. Then we focus on an instance of the problem of rewriting conjunctive queries using views through an ontology expressed in a description logic, for which we exhibit a complete algorithm

In many application scenarios, the use of the Web ontology language OWL is hampered by the complexity of the underlying logic that makes reasoning in OWL intractable in the worst case. In this paper, we address the question whether approximation techniques known from the knowledge representation literature can help to simplify OWL reasoning. In particular, we carry out experiments with approximate deduction techniques on the problem of classifying new concept expressions into an existing OWL ontology using existing Ontologies on the web. Our experiments show that a direct application of approximate deduction techniques as proposed in the literature in most cases does not lead to an improvement and that these methods also suffer from some fundamental problems.

In has been argued that ontologies play a key role in multiagent communication because they provide and define a shared vocabulary to be used in the course of communication. In real-life scenarios, however, the situation where two agents completely share a vocabulary is rather an exception. More often, each agent uses its own vocabulary specified in a private ontology that is not known by other agents. In this paper we propose a solution to this problem for the situation, where agents share at least parts of their vocabulary. We argue that the assumption of a partially shared vocabulary is valid and sketch an approach for re-formulating terms from the private part of an agent's ontology into a shared part thus enabling other agents to understand them. We further describe how the approach can be implemented using existing technology and proof the correctness of the re-formulation with respect to the semantics of the ontology-language DAML+OIL.

Approximating a concept, de ned in one DL, means to translate this concept to another concept, de ned in a second typically less expressive DL, such that both concepts are as closely related as possible with respect to subsumption. In a previous work, we have provided an algorithm for approximating ALC-concept descriptions by ALE-concept descriptions. In the present paper, motivated by an application in chemical process engineering, we extend this result by taking number restrictions into account.

As part of the MKBEEM project, we present an ontology based mediation framework for electronic commerce applications. The framework is based on a mediator/wrapper approach that supports an integrated view over multiple heterogeneous sources. The MKBEEM mediation system allows to fill the gap between customers queries (possibly expressed in a natural language) and diverse specific providers o#ers. In contrast with many existing mediator based systems, our approach rests on a three-layer knowledge representation architecture which includes an electronic services ontology besides the usual domain ontology and sources descriptions layers. At the reasoning level, we propose a new mechanism, namely dynamic discovery of e-services, that acts in collaboration with the Picsel mediator system to e#ectively achieve the MKBEEM mediation tasks.