BibSonomy publications for /author/BrunzelFri Oct 01 13:29:38 CEST 2010Task Management Model - Nepomuk Deliverable D3.12006d3.1 deliverable nepomuk Tue May 19 00:00:00 CEST 2009Wirtschaftsinformatik4303-305Auf dem Weg von der aufgabenorientierten zur prozessorientierten Verwaltung auf Grundlage Service-orientierter E-Government-Architekturen.482006dblp Sun Apr 26 18:00:58 CEST 2009J. Data Semanticsjournals/jods/2008-11J. Data Semantics126-155Lecture Notes in Computer ScienceDiscovering Groups of Sibling Terms from Web Documents with XTREEM-SG.112008coordinates sibling_groups sibling_relations Tue Mar 31 00:00:00 CEST 2009J. Data Semanticsjournals/jods/2008-11J. Data Semantics126-155Lecture Notes in Computer ScienceDiscovering Groups of Sibling Terms from Web Documents with XTREEM-SG.112008dblp Tue Mar 10 00:00:00 CET 2009RIAOconf/riao/2004156-169Coupling Information Extraction and Data Mining for Ontology Learning in PARMENIDES.2004dblp Mon Dec 08 02:43:48 CET 2008Task Management Model - Nepomuk Deliverable D3.12006task_management Tue Sep 23 00:00:00 CEST 2008VISUALconf/visual/2008315-318Lecture Notes in Computer ScienceHandling of Task Hierarchies on the Nepomuk Social Semantic Desktop.51882008dblp Tue Aug 28 00:00:00 CEST 2007DaWaKconf/dawak/2007365-374Lecture Notes in Computer ScienceLearning of Semantic Sibling Group Hierarchies - K-Means vs. Bi-secting-K-Means.46542007dblp Fri Aug 24 00:00:00 CEST 2007NLDBconf/nldb/2007427-432Lecture Notes in Computer ScienceDomain Relevance on Term Weighting.45922007dblp Fri Jul 06 10:33:42 CEST 2007Proc. of European Conference on the Semantic Web (ECSW 2005)RELFIN - Topic Discovery for Ontology Enhancement and Annotation2005no-tag Wed Jun 13 10:38:51 CEST 2007LNAI 4248Discovering Semantic Sibling Groups from Web Documents with XTREEM-SG20062006 co-hyponymy co-meronymy ontology ontology-enhancement ontology-learning semantic-siblings semi-structured sibling-groups The acquisition of explicit semantics is still a research challenge. Approaches for the extraction of semantics focus mostly on learning hierarchical hypernym-hyponym relations. The extraction of co-hyponym and co-meronym sibling semantics is performed to a much lesser extent, though they are not less important in ontology engineering. In this paper we will describe and evaluate the XTREEM-SG (Xhtml TREE Mining - for Sibling Groups) approach on finding sibling semantics from semistructured Web documents. XTREEM takes advantage of the added value of mark-up, available in web content, for grouping text siblings. We will show that this grouping is semantically meaningful. The XTREEM-SG approach has the advantage that it is domain and language independent; it does not rely on background knowledge, NLP software or training. In this paper we apply the XTREEM-SG approach and evaluate against the reference semantics from two golden standard ontologies. We investigate how variations on input, parameters and reference influence the obtained results on structuring a closed vocabulary on sibling relations. Earlier methods that evaluate sibling relations against a golden standard report a 14.18% F-measure value. Our method improves this number into 21.47%.Wed Jun 13 10:37:56 CEST 200712th International Conference on Applications of Natural Language to Information Systems (NLDB) June 27-29, 2007, CNAM, Paris, FranceLecture Notes in Computer ScienceDomain Relevance on Term Weighting4592200704 2006 dfki from:biberburg wp2 The TFxIDF term weighting scheme is the standard approach on vectorization of textual data. For a data set where textual data stemming from web document structure is to be vectorized \cite{DBLP:conf/kdxd/BrunzelS06} the need for a enhanced term weighting scheme arose. In this publication we introduce a term weighting scheme which improves the behavior compared to the traditional TFxIDF scheme by adding a component which is based on the linguistically inspired notion of domain relevance. Domain relevance measures the degree to which a term is regarded as more relevant within a data set compared to a reference data set. By means of this external component a potential weakness of TFxIDF on non standard distributed data sets is overcome. This weighting scheme favours domain relevant terms, which can be regarded as more useful in settings where the clustering is performed to be consumed by an human supervisor e.g for semi-automatic ontology learning.Mon Jun 11 19:44:18 CEST 20074th Conference on Professional Knowledge Management - Experiences and Visions -, March 28. - 30. 2007, Potsdam, GermanyTask Management for the NEPOMUK Social Semantic Desktop (Poster)200703 2007 NEPOMUK SAP Semantic Social WP10 announce desktop from:ogr lang:en pattern poster task taskmanagement Mon Jun 11 19:33:32 CEST 20074th Conference on Professional Knowledge Management - Experiences and Visions -, March 28. - 30. 2007, Potsdam, GermanyTask Management for the NEPOMUK Social Semantic Desktop (Poster)200703 2007 NEPOMUK SAP Semantic Social WP10 announce desktop lang:en pattern poster task taskmanagement Wed Nov 29 00:00:00 CET 2006EWMF/KDOconf/ewmf/2005132-146Lecture Notes in Computer ScienceEvaluation of Ontology Enhancement Tools.42892005dblp Mon Oct 30 00:00:00 CET 2006DaWaKconf/dawak/2006469-480Lecture Notes in Computer ScienceDiscovering Semantic Sibling Associations from Web Documents with XTREEM-SP.40812006dblp Tue Oct 24 00:00:00 CEST 2006EKAWconf/ekaw/2006141-157Lecture Notes in Computer ScienceDiscovering Semantic Sibling Groups from Web Documents with XTREEM-SG.42482006dblp Wed Mar 01 00:00:00 CET 2006KDXDconf/kdxd/200622-32Lecture Notes in Computer ScienceDiscovering Multi Terms and Co-hyponymy from XHTML Documents with XTREEM.39152006dblp Tue May 24 00:00:00 CEST 2005ESWCconf/esws/2005608-622Lecture Notes in Computer ScienceRELFIN - Topic Discovery for Ontology Enhancement and Annotation.35322005dblp