http://www.bibsonomy.org/burst/user/pitman/knowledgeBibSonomy BuRST Feed for /user/pitman/knowledge2008-10-16T07:01:46+02:00SpringerLink - Book Chapterhttp://www.bibsonomy.org/bibtex/2d5a40499a2e9d108d1db9bb656c296e2/pitmanpitman2008-08-10T19:03:37+02:00platform knowledge ontology management engineering <span style="color:#555555;">Gary <a href="http://www.bibsonomy.org/author/Merrill">Merrill</a> </span><em>Ontologies: A Handbook of Principles, Concepts and Applications in Information Systems, </em><em>Springer, </em>(<em>2007</em>)Sun Aug 10 19:03:37 CEST 2008Ontologies: A Handbook of Principles, Concepts and Applications in Information Systems777--822Engineering a Development Platform for Ontology-Enhanced Knowledge Applications2007platform knowledge ontology management engineering Babylon Knowledge Explorer (BKE) is an integrated suite of tools and information sources being developed in GlaxoSmithKline’shttp://www.bibsonomy.org/bibtex/2bb32615a0ff514d2f97eb58d52af51df/pitmanpitman2008-08-08T03:18:35+02:00knowledge community local bkn <span style="color:#555555;">Robin <a href="http://www.bibsonomy.org/author/Boast">Boast</a> und Michael <a href="http://www.bibsonomy.org/author/Bravo">Bravo</a> und Ramesh <a href="http://www.bibsonomy.org/author/Srinivasan">Srinivasan</a> </span><em>The Information Society</em>(<em>2007</em>)Fri Aug 08 03:18:35 CEST 2008The Information Society395Return to Babel: Emergent Diversity, Digital Resources, and Local Knowledge232007knowledge community local bkn http://www.bibsonomy.org/bibtex/298dea1ae9f54161eeb1c18d318ae5dcb/pitmanpitman2008-01-13T18:00:15+01:00relatedness knowledge semantic_web Wikipedia <span style="color:#555555;">Simone Paolo <a href="http://www.bibsonomy.org/author/Ponzetto">Ponzetto</a> und Michael <a href="http://www.bibsonomy.org/author/Strube">Strube</a> </span><em>Journal of Artificial Intelligence Research</em>(<em>2007</em>)Sun Jan 13 18:00:15 CET 2008Journal of Artificial Intelligence Research181-212Knowledge Derived from Wikipedia for Computing Semantic Relatedness302007relatedness knowledge semantic_web Wikipedia Wikipedia provides a semantic network for computing semantic relatedness in a more structured fashion than a search engine and with more coverage than WordNet. We present experiments on using Wikipedia for computing semantic relatedness and compare it to WordNet on various benchmarking datasets. Existing relatedness measures perform better using Wikipedia than a baseline given by Google counts, and we show that Wikipedia outperforms WordNet on some datasets. We also address the question whether and how Wikipedia can be integrated into NLP applications as a knowledge base. Including Wikipedia improves the performance of a machine learning based coreference resolution system, indicating that it represents a valuable resource for NLP applications. Finally, we show that our method can be easily used for languages other than English by computing semantic relatedness for a German dataset.