BibSonomyburst/user/eswc2008/dataBibSonomy RSS feed for /user/eswc2008/data2012-02-16T05:08:27+01:00http://www.bibsonomy.org/bibtex/2fc7f36c61174d07ed9bdb4608c250284/eswc2008eswc20082008-05-28T14:50:00+02:00processing data mediator integration distributed sparql query semantic web query-processing-2 <span class="authorEditorList"><a href="/author/Langegger">Andreas Langegger</a>, <a href="/author/Wöß">Wolfram Wöß</a>, and <a href="/author/Blöchl">Martin Blöchl</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:50:00 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSA Semantic Web Middleware for Virtual Data Integration on the Web2008processing data mediator integration distributed sparql query semantic web query-processing-2 In this contribution a system is presented, which provides access to distributed data sources using Semantic Web technology. While it was primarily designed for data sharing and scientific collaboration, it is regarded as a base technology useful for many other Semantic Web applications. The proposed system allows to retrieve data using SPARQL queries, data sources can register and abandon freely, and all RDF Schema or OWL vocabularies can be used to describe their data, as long as they are accessible on the Web. Data heterogeneity is addressed by RDF-wrappers like D2R-Server placed on top of local information systems. A query does not directly refer to actual endpoints, instead it contains graph patterns adhering to a virtual data set. A mediator finally pulls and joins RDF data from different endpoints providing a transparent on-the-fly view to the end-user. The SPARQL protocol has been defined to enable systematic data access to remote endpoints. However, remote SPARQL queries require the explicit notion of endpoint URIs. The presented system allows users to execute queries without the need to specify target endpoints. Additionally, it is possible to execute join and union operations across different remote endpoints. The optimization of such distributed operations is a key factor concerning the performance of the overall system. Therefore, proven concepts from database research can be applied.http://www.bibsonomy.org/bibtex/27e0e8278793cb68e516ee4a564445bd9/eswc2008eswc20082008-05-28T14:50:00+02:00semantic claim linked open authoring web federation data applications-1 <span class="authorEditorList"><a href="/author/Groza">Tudor Groza</a>, <a href="/author/Handschuh">Siegfried Handschuh</a>, <a href="/author/Möller">Knud Möller</a>, and <a href="/author/Decker">Stefan Decker</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:50:00 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSKonneX-SALT: First Steps towards a Semantic Claim Federation Infrastructure2008semantic claim linked open authoring web federation data applications-1 Dissemination, an important phase of scientific research, can be seen as a communication process between scientists. They expose and support their findings, while discussing claims stated in related scientific publications. However, due to the increasing number of publications, finding a starting point for such a discussion represents a real challenge. At same time, browsing can also be difficult since the communication spans across multiple publications on the open web. In this paper we propose a semantic claim federation infrastructure, named KonneX-SALT, as a solution for both issues mentioned above: (i) finding claims in scientific publications, and (ii) building the argumentation discourse network (ADN) for each claim and providing support for browsing it (in our case, by making use of transclusion). In addition, we join the web of "linked open data", by linking the metadata managed by KonneX-SALT with some of the known repositories of scientific publications.http://www.bibsonomy.org/bibtex/2dc85f0d776078a6b46419598834afa09/eswc2008eswc20082008-05-28T14:49:54+02:00adaptation applications data internet language mining modeling ontologies rich rule semantic user user-interfaces-and-personalization web <span class="authorEditorList"><a href="/author/Schmidt">Kay-Uwe Schmidt</a>, <a href="/author/Dörflinger">Jörg Dörflinger</a>, <a href="/author/Rahmani">Tirdad Rahmani</a>, <a href="/author/Sahbi">Mehdi Sahbi</a>, <a href="/author/Thomas">Susan Thomas</a>, and <a href="/author/Stojanovic">Ljiljana Stojanovic</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:49:54 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSAn User Interface Adaptation Architecture for \\Rich Internet Applications2008adaptation applications data internet language mining modeling ontologies rich rule semantic user user-interfaces-and-personalization web The need for adaptive and personalized Rich Internet Application puts a new dimension to already existing approaches of Adaptive Hypermedia Systems. Instead of computing the adaptation steps at the server, Rich Internet Applications need a client-side approach that can react immediately on user input. In this paper we present a novel approach that holistically combines page annotations, semantic Web usage mining, user modeling, ontologies and rules to adapt AJAX pages. The focus of our pater is the conceptual introduction of the autonomous client. An autonomous client directly executes all necessary adaptation steps based on a user model, without requesting any logic on the server. In order to realize this, we use ontologies to annotate Rich Internet Applications and to describe the user model as well as semantic Web usage mining for detecting adaptation rules. Additionally, we provide a detailed overview and evaluation of how we moved resource-intensive ontology processing and rules execution from the server to the client.http://www.bibsonomy.org/bibtex/270a327927af4ed4bee7c7731ae066dd3/eswc2008eswc20082008-05-28T14:49:53+02:00storage sw versioning data foundational-issues-storage-and-retrieval <span class="authorEditorList"><a href="/author/Tzitzikas">Yannis Tzitzikas</a>, <a href="/author/Theoharis">Yannis Theoharis</a>, and <a href="/author/Andreou">Dimitris Andreou</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:49:53 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSOn Storage Policies for Semantic Web Repositories that Support Versioning2008storage sw versioning data foundational-issues-storage-and-retrieval This paper concerns versioning services over Semantic Web repositories. At first we introduce an abstract model of versioning services and subsequently we elaborate on storage policies for enabling these services. Specifically, we propose a novel storage policy that exploits the fact that RDF graphs have not a unique serialization (as it happens with texts). For this reason we introduce a storage structure for versioning that is based on partial orders. We discuss the comparative benefits and drawbacks of this approach in terms of storage space and efficiency both analytically and experimentally. For the latter case we report experimental results over large synthetic data sets and we provide efficient algorithms for version creation and retrieval.http://www.bibsonomy.org/bibtex/2569e52ad749e5ea312aae2a76dca52d7/eswc2008eswc20082008-05-28T14:49:52+02:00sparql data statistical evaluation mining relational learning query-processing-1 <span class="authorEditorList"><a href="/author/Kiefer">Christoph Kiefer</a>, <a href="/author/Bernstein">Abraham Bernstein</a>, and <a href="/author/Locher">André Locher</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:49:52 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSAdding Data Mining Support to SPARQL via Statistical Relational Learning Methods2008sparql data statistical evaluation mining relational learning query-processing-1 In machine learning/data mining, people have been exploring how to learn models of relational data for a long time. The rational behind this is that exploiting the rich and complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. These links are usually hard to model by traditional propositional learning techniques. We extend this idea to the Semantic Web. In this paper we introduce a novel approach we call SPARQL-ML to perform data mining for Semantic Web data. Our approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers. We analyze our approach thoroughly conducting three sets of experiments on synthetic as well as real-world datasets. Our analytical results show that our approach can be used for any Semantic Web dataset to perform instance-based learning and classification. A comparison to kernel methods used in Support Vector Machines shows that our approach is superior in terms of classification accuracy. Moreover, we show how our approach can be used for Semantic Web service classification and automatic semantic annotation.