BibSonomyburst/user/eswc2008/retrievalBibSonomy RSS feed for /user/eswc2008/retrieval2012-02-16T16:25:33+01:00http://www.bibsonomy.org/bibtex/2771947296490ffa6cd01ada59cb6c1ec/eswc2008eswc20082008-05-28T14:50:06+02:00ontology end-to-end cultural retrieval evaluation semantic alignment heritage methods distance ontology-alignment <span class="authorEditorList"><a href="/author/Hollink">Laura Hollink</a>, <a href="/author/van Assem">Mark van Assem</a>, <a href="/author/Isaac">Antoine Isaac</a>, <a href="/author/Wang">Shenghui Wang</a>, and <a href="/author/Schreiber">Guus Schreiber</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 14:50:06 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSTwo Variations on Ontology Alignment Evaluation: Methodological Issues2008ontology end-to-end cultural retrieval evaluation semantic alignment heritage methods distance ontology-alignment Evaluation of ontology alignments is in practice done in two ways: (1) assessing individual correspondences and (2) comparing the alignment to a reference alignment. However, this type of evaluation does not guarantee that an application which uses the alignment will perform well. In this paper, we contribute to the current ontology alignment evaluation practices by proposing two alternative evaluation methods that take into account some characteristics of a usage scenario without doing a full-fledged end-to-end evaluation. We compare different evaluation approaches in three case studies, focussing on methodological issues. Each case study considers an alignment between a different pair of ontologies, ranging from rich and well-structured to small and poorly structured. This enables us to conclude on the use of different evaluation approaches in different settings.http://www.bibsonomy.org/bibtex/2e89c1407d23363623b309b221e2ca1e9/eswc2008eswc20082008-05-28T14:50:00+02:00document semantic search spreading desktop activation retrieval <span class="authorEditorList"><a href="/author/Schumacher">Kinga Schumacher</a>, <a href="/author/Sintek">Michael Sintek</a>, and <a href="/author/Sauermann">Leo Sauermann</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 ConferenceJuneLNCSCombining Meta Data and Document Search with Spreading Activation for Semantic Desktop Search2008document semantic search spreading desktop activation retrieval The Semantic Desktop is a means to support users in Personal Information Management (PIM). It provides an excellent test bed for Semantic Web technology: resources (e. g., persons, projects, messages, documents) are distributed amongst multiple systems, ontologies are used to link and annotate them. Finding information is a core element in PIM. For the end user, the search interface has to be intuitive to use, natural language queries provide a simple mean to express requests. State of the art semantic search engines focus on metadata search or on semantic document retrieval. We combine both approaches to search the Semantic Desktop exploiting all available information, where we build on semantic teleporting and spreading activation. This combination is able to answer queries with instances, subgraphs of the knowledge base, and with relevant documents. We evaluated our approach on ESWC 2007 data in comparison with Google site search.http://www.bibsonomy.org/bibtex/24058a55f996d8c24ef69c32f3c81ccdd/eswc2008eswc20082008-05-28T14:49:57+02:00retrieval information matchmaking machine learning sparql evaluation query-processing-1 <span class="authorEditorList"><a href="/author/Kiefer">Christoph Kiefer</a>, and <a href="/author/Bernstein">Abraham Bernstein</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 ConferenceJuneLNCSThe Creation and Evaluation of iSPARQL Strategies for Matchmaking2008retrieval information matchmaking machine learning sparql evaluation query-processing-1 This research explores our novel method for Semantic Web service matchmaking based on iSPARQL queries, which enable the user to query the Semantic Web with techniques from traditional information retrieval. The strategies for matchmaking which we develop and evaluate in the paper make use of a plethora of similarity measures and combination functions from SimPack -- our library of similarity measures for the use in ontologies. We show how our combination of structured and imprecise querying can be used to perform hybrid Semantic Web service matchmaking in simple and amazingly fast fashion. We analyze our approach thoroughly on a large OWL-S service test collection, and show how our initial strategies can be improved by applying machine learning algorithms such as regression, decision trees, or support vector machines to result in the most effective strategies for matchmaking.