<div id="header"><h1>Nature inspired Reasoning for the Semantic Web (NatuReS)</h1>
<p><strong>at the <a href="http://iswc2008.semanticweb.org">7th international Semantic Web Conference (ISWC 2008)</a>, Karlsruhe, Germany</strong></p>
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<h1><a name="list_of_accepted_papers" id="list_of_accepted_papers">List of accepted papers</a></h1>
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<li class="level1"><div class="li"> <a href="http://natures.few.vu.nl/files/Paper_2.ppt" class="urlextern" title="http://natures.few.vu.nl/files/Paper_2.ppt" rel="nofollow">Optimizing Ontology Alignments by Using Genetic Algorithms</a></div>
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Jorge Martinez-Gil, Enrique Alba and Jose F Aldana Montes.
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<li class="level1"><div class="li"> <a href="http://natures.few.vu.nl/files/Paper_3.ppt" class="urlextern" title="http://natures.few.vu.nl/files/Paper_3.ppt" rel="nofollow">Genetic Algorithms for RDF Query Path Optimization</a></div>
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Alexander Hogenboom, Viorel Milea, Flavius Frasincar and Uzay Kaymak.
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<li class="level1"><div class="li"> <a href="http://natures.few.vu.nl/files/Paper_4.ppt" class="urlextern" title="http://natures.few.vu.nl/files/Paper_4.ppt" rel="nofollow">Anatomy of a Semantic Virus</a></div>
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Peyman Nasirifard.
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<li class="level1"><div class="li"> <a href="http://natures.few.vu.nl/files/Paper_6.ppt" class="urlextern" title="http://natures.few.vu.nl/files/Paper_6.ppt" rel="nofollow">Text-Based Ontology Enrichment Using Hierarchical Self-organizing Maps</a></div>
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Emil St. Chifu and Ioan Alfred Letia.
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<li class="level1"><div class="li"> <strong>Human Similarity theories for the semantic web</strong></div>
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Jose Quesada.
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<h1><a name="invited_speakers" id="invited_speakers">Invited speakers</a></h1>
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<h2><a name="nature-inspired_optimization_-_and_what_it_might_do_for_you" id="nature-inspired_optimization_-_and_what_it_might_do_for_you">Nature-inspired optimization - and what it might do for you</a></h2>
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<li class="level1"><div class="li"> <strong>Speaker</strong> : <a href="http://www.aifb.uni-karlsruhe.de/%7Ejbr/jbr.engl.html" class="urlextern" title="http://www.aifb.uni-karlsruhe.de/~jbr/jbr.engl.html" rel="nofollow">PD Dr. Jürgen Branke</a>, Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Universität Karlsruhe (TH), Karlsruhe, Germany</div>
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<li class="level1"><div class="li"> <strong>Date</strong> : pm 27.10.2008</div>
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<li class="level1"><div class="li"> <strong>Presentation</strong> : <a href="http://natures.few.vu.nl/files/NOV-WhatItCanDo.pdf" class="urlextern" title="http://natures.few.vu.nl/files/NOV-WhatItCanDo.pdf" rel="nofollow">Slides of the presentation</a></div>
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<h2><a name="why_nature_inspired_paradigms_in_reasoning_and_learning_are_necessary" id="why_nature_inspired_paradigms_in_reasoning_and_learning_are_necessary">Why Nature Inspired Paradigms in Reasoning and Learning are Necessary</a></h2>
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<li class="level1"><div class="li"> <strong>Speaker</strong> : <a href="http://www.cogsci.uni-osnabrueck.de/%7Ekkuehnbe/" class="urlextern" title="http://www.cogsci.uni-osnabrueck.de/~kkuehnbe/" rel="nofollow">Prof. Dr. Kai-Uwe Kühnberger</a> Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany</div>
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<li class="level1"><div class="li"> <strong>Date</strong> : am 27.10.2008 </div>
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<li class="level1"><div class="li"> <strong>Abstract</strong> : Classical reasoning and learning methods are often cognitively implausible. Even worse, classical problems like the variety of different types of reasoning and learning, complexity issues of reasoning and learning, profusion of knowledge and representation formalisms, and learning from sparse and noisy data often challenge classical approaches in practical applications. This makes the need of new computing paradigms necessary. This presentation will give some ideas (clearly no ready-made solutions) for cognitively motivated and nature inspired candidates to resolve some of the mentioned problems: <acronym title="Document Object Model">DOM</acronym> tree learning with support vector machines can be used to classify text genres, neural-symbolic integration is a tool to learn logical inferences with neural networks, and analogical reasoning is a candidate for the integration of various reasoning types. Promising application domains for such approaches may be text technology, semantic web, and ontology design.</div></li></ul></div></div>
