http://www.bibsonomy.org/burst/user/eswc2008/rdfBibSonomy RSS feed for /user/eswc2008/rdf2010-03-17T22:47:50+01:00http://www.bibsonomy.org/bibtex/2e672f158fc594179cd9fd36f8a135de4/eswc2008eswc20082008-05-28T14:50:05+02:00instant agent sparql xmpp rdf messaging agents-application-ontologies <span style="color:#555555;">Sebastian <a href="http://www.bibsonomy.org/author/Dietzold">Dietzold</a> and J&#246;rg <a href="http://www.bibsonomy.org/author/Unbehauen">Unbehauen</a> and S&#246;ren <a href="http://www.bibsonomy.org/author/Auer">Auer</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 14:50:05 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSxOperator - Interconnecting the Semantic Web and Instant Messaging Networks2008instant agent sparql xmpp rdf messaging agents-application-ontologies Instant Messaging is in addition to Web and Email the most popular service on the Internet. With xOperator we present a strategy and implementation which deeply integrates Instant Messaging networks with the Semantic Web. The xOperator concept is based on the idea of creating an overlay network of collaborative information agents on top of social IM networks. It can be queried using a controlled and easily extensible language based on AIML templates. Such a deep integration of semantic technologies and Instant Messaging bears a number of advantages and benefits for users when compared to the separated use of Semantic Web technologies and IM, the most important ones being context awareness as well as provenance and trust. We showcase how the xOperator approach naturally facilitates contacts and calendar management as well as access to large scale heterogeneous information sources.http://www.bibsonomy.org/bibtex/21a97459b80d2cac3fd8b935452fe0418/eswc2008eswc20082008-05-28T14:50:01+02:00rdf measure clustering distance learning <span style="color:#555555;">Gunnar <a href="http://www.bibsonomy.org/author/Grimnes">Grimnes</a> and Peter <a href="http://www.bibsonomy.org/author/Edwards">Edwards</a> and Alun <a href="http://www.bibsonomy.org/author/Preece">Preece</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 14:50:01 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSDistance Based clustering of Semantic Web Resources2008rdf measure clustering distance learning The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue that an essential feature for such agents is the capability to analyse data and learn. In this paper we outline the challenges and issues surrounding the application of clustering algorithms to Semantic Web data. We present several ways to extract instances from a large RDF graph and computing the distance between these. We evaluate our approaches on three different data-sets, one representing a typical relational database to RDF conversion, one based on data from a ontologically rich Semantic Web enabled application, and one consisting of a crawl of FOAF documents; applying both supervised and unsupervised evaluation metrics. Our evaluation did not support choosing a single combination of instance extraction method and similarity metric as superior in all cases, and as expected the behaviour depends greatly on the data being clustered. Instead, we attempt to identify characteristics of data that make particular methods more suitable.http://www.bibsonomy.org/bibtex/254b3e29ce6a6f65fd0cd595a0904f919/eswc2008eswc20082008-05-28T14:49:57+02:00rdf semantic h-subsumption web entailment complexity formal-languages-2 <span style="color:#555555;">Reinhard <a href="http://www.bibsonomy.org/author/Pichler">Pichler</a> and Axel <a href="http://www.bibsonomy.org/author/Polleres">Polleres</a> and Fang <a href="http://www.bibsonomy.org/author/Wei">Wei</a> and Stefan <a href="http://www.bibsonomy.org/author/Woltran">Woltran</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 14:49:57 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSEntailment for Domain-restricted RDF2008rdf semantic h-subsumption web entailment complexity formal-languages-2 We introduce domain-restricted RDF (dRDF) which allows to associate an RDF graph with a fixed, finite domain that interpretations for it may range over. We show that dRDF is a real extension of RDF and discuss impacts on the complexity of entailment in dRDF. The entailment problem represents the key reasoning task for RDF and is well known to be NP-complete. Remarkably, we show that the restriction of domains in dRDF raises the complexity of entailment from NP- to $\Pi^P_2$-completeness. In order to lower complexity of entailment for both domain-restricted and unrestricted graphs, we take a closer look at the graph structure. For cases where the structure of RDF graphs is restricted via the concept of bounded treewidth, we manage to prove tractability of entailment. We also present a polynomial entailment checking algorithm for such graphs.http://www.bibsonomy.org/bibtex/20164f0b77530f4b038a71c7fa3ad6546/eswc2008eswc20082008-05-28T14:49:50+02:00processing sparql stream rdf query-processing-1 <span style="color:#555555;">Andre <a href="http://www.bibsonomy.org/author/Bolles">Bolles</a> and Marco <a href="http://www.bibsonomy.org/author/Grawunder">Grawunder</a> and Jonas <a href="http://www.bibsonomy.org/author/Jacobi">Jacobi</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 14:49:50 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSStreaming SPARQL - Extending SPARQL to process data streams2008processing sparql stream rdf query-processing-1 A lot of work has been done in the area of data stream processing. Most of the previous approaches regard only relational or XML based streams but do not cover semantic richer RDF based stream elements. In our work, we extend SPARQL, the W3C recommendation for an RDF query language, to process RDF data streams. To describe the semantics of our enhancement, we extended the logical SPARQL algebra for stream processing on the foundation of a temporal relational algebra based on multi sets and provide an algorithm to transform SPARQL queries to the new extended algebra. For each logical algebra operator, we defined executable physical counterparts. To show the feasibility of our approach, we implemented it within our ODYSSEUS framework in the context of wind power plant monitoring.