for different types of linguistic descriptions. In this contribution we propose a new module to represent translation relations between lexicons in different natural languages associated to the same ontology or belonging to different ontologies. This module can enable the representation of different types

), an image retrieval system, which uses semantics classification methods, a wavelet-based approach for feature extraction, and integrated region matching based upon image segmentation. As in other regionbased retrieval systems, an image is represented by a set of regions, roughly corresponding to objects

The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic

XML is fast emerging as the dominant standard for representing data in the World Wide Web. Sophisticated query engines that allow users to effectively tap the data stored in XML documents will be crucial to exploiting the full power of XML. While there has been a great deal of activity recently

An important objective of the Semantic Web is to make Electronic Commerce interactions more flexible and automated. To achieve this, standardisation of ontologies, message content and message protocols will be necessary. In this paper we investigate how Semantic and Web Services technologies can

We describe our method for benchmarking Semantic Web knowledge base systems with respect to use in large OWL applications. We present the Lehigh University Benchmark (LUBM) as an example of how to design such benchmarks. The LUBM features an ontology for the university domain, synthetic OWL data

formally define the semantics of credentials in the RT framework by presenting a translation from credentials to Datalog rules. This translation also shows that this semantics is algorithmically tractable. 1

We present a novel framework for mapping between any combination of XML and relational schemas, in which a high-level, userspecified mapping is translated into semantically meaningful queries that transform source data into the target representation. Our approach works in two phases. In the first

The potential to achieve dynamic, scalable and cost-effective marketplaces and eCommerce solutions has driven recent research efforts towards so-called Semantic Web Services, that are enriching Web services with machine-processable semantics. To this end, the Web Service Modeling Ontology (WSMO

Web information is represented today. We need a Semantic Web to express information in a precise, machine-interpretable form, so software agents processing the same set of data share an understanding of what the terms describing the data mean.