USC Information Sciences Institute 4676 Admirality Way, Marina Del Rey United States Knowledge Representation Languages Titel:Trusting Information Sources One Citizen at a Time This paper describes an approach to derive assessments about information sources based on individual feedback about the sources. We describe TRELLIS, a system that helps users annotate their analysis of alternative information sources that can be contradictory and incomplete. As the user makes a decision on which sources to dismiss and which to believe in making a final decision, TRELLIS captures the derivation of the decision in a semantic markup. TRELLIS then uses these annotations to derive an assessment of the source based on the annotations of many individuals. Our work builds on the Semantic Web and presents a tool that helps users create annotations that are in a mix of formal and human language, and exploits the formal representations to derive measures of trust in the content of Web resources and their original source. International Semantic Web Conference 2002 Sardinia June 9-12, 2002 Semantic Annotation Semantic Web Semantic Web Languages Web Services World Wide Web Artificial Intelligence Knowledge Systems Titel:Integrating Vocabularies: Discovering and Representing Vocabulary Maps The Semantic Web would enable new ways of doing business on the<br>Web that require development of advanced business document<br>integration technologies performing intelligent document<br>transformation. The documents use different vocabularies that<br>consist of large hierarchies of terms. Accordingly, vocabulary<br>mapping and transformation becomes an important task in the whole<br>business document transformation process. It includes several<br>subtasks: map discovery, map representation, and map execution<br>that must be seamlessly integrated into the document integration<br>process. In this paper we discuss the process of discovering the<br>maps between two vocabularies assuming availability of two sets of<br>documents, each using one of the vocabularies. We take the<br>vocabularies of product classification codes as a playground and<br>propose a reusable map discovery technique based on Bayesian text<br>classification approach. We show how the discovered maps can be<br>integrated into the document transformation process. Semantic Web Infrastructure E-Business Vrije Universiteit, Division of Mathematics and Computer Science, De Boelelaan 1081a,1081hv, Amsterdam, The Netherlands Titel:A Data Integration Framework for E-commerce Product Classification A marketplace is the place in which the demand and supply of buyers and vendors participating in a business process may meet. Therefore, electronic marketplaces are virtual communities in which buyers may meet proposals of several suppliers and make the best choice. In the electronic commerce world, the comparison between different products is blocked due to the lack of standards (on the contrary, the proliferation of standards) describing and classifying them. Therefore, the need for B2B and B2C marketplaces is to reclassify products and goods according to different standardization models. This paper aims to face this problem by suggesting the use of a semi-automatic methodology, supported by a tool (SI-Designer), to define the mapping among different e-commerce product classification standards. This methodology was developed for the MOMIS-system within the Intelligent Integration of Information research area. We describe our extension to the methodology that makes it applyable in general to product classification standard, by selecting a fragment of ECCMA/UNSPSC and ecl@ss standard. Databases DII- Universita di Modena e Reggio Emilia via Vignolese 905 41100 Modena +39 059 2056132 Knowledge Management DII- Universita di Modena e Reggio Emilia via Vignolese 905 41100 Modena Italy +39 059 20561543 Dipartimento di Ingegneria dell'Informazione Via Vignolese 905 – Modena Italy Institute for the Protection and Security of the Citizen Institute for the Protection and Security of the Citizen Via Enrico Fermi, 1 21020 - Ispra (Italy) Titel:Three Implementations of SquishQL, a Simple RDF Query Language RDF provides a basic way to represent data for the Semantic Web. We have been experimenting with the query paradigm for working with RDF data in semantic web applications. Query of RDF data provides a declarative access mechanism that is suitable for application usage and remote access. We describe work on a conceptual model for querying RDF data that refines ideas first presented in at the W3C workshop on Query Languages and the design of one possible syntax, derived from rdfDB, that is suitable for application programmers. Further, we present experience gained in three implementations of the query language. Hewlett-Packard Laboratories, Bristol, BS34 8QZ, UK Query Languages Universiteit Amsterdam De Boelelaan 1105 The Netherlands International University in Germany International University in Germany Campus 2 76646 Bruchsal Germany +49 7251 700 222 Titel:Automatic Generation of Java/SQL based Inference Engines from RDF Schema and RuleML This paper describes two approaches for automatically converting RDF Schema and RuleML sources into an inference engine and storage repository. Rather than using traditional inference systems, our solution bases on mainstream technologies like Java and relational database systems. While this necessarily imposes some restrictions, the ease of integration into an existing IT landscape is a major advantage. We present the conversion tools and their limitations. Furthermore, an extension to RuleML is proposed, that allows Java-enabled reaction rules, where calls to Java libraries can be performed upon a rule firing. This requires hosts to be Java-enabled when rules and code are moved across the web. However, the solution allows for great engineering flexibility. Text Mining XML Hewlett-Packard Laboratories, Bristol Department of Computer Science De Boelelaan 1081a The Netherlands