PUMA publications for /user/benz/relatednesshttps://puma.uni-kassel.de/user/benz/relatednessPUMA RSS feed for /user/benz/relatedness2024-03-29T06:02:07+01:00A study on similarity and relatedness using distributional and WordNet-based approacheshttps://puma.uni-kassel.de/bibtex/2e91cce045a1d323c0012027f04771733/benzbenz2011-02-21T23:23:16+01:00distributional relatedness semantic_similarity similarity wordnet <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Eneko Agirre" itemprop="url" href="/author/Eneko%20Agirre"><span itemprop="name">E. Agirre</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Enrique Alfonseca" itemprop="url" href="/author/Enrique%20Alfonseca"><span itemprop="name">E. Alfonseca</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Keith Hall" itemprop="url" href="/author/Keith%20Hall"><span itemprop="name">K. Hall</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jana Kravalova" itemprop="url" href="/author/Jana%20Kravalova"><span itemprop="name">J. Kravalova</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Marius Pasca" itemprop="url" href="/author/Marius%20Pa%5cc%7bs%7dca"><span itemprop="name">M. Pasca</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Aitor Soroa" itemprop="url" href="/author/Aitor%20Soroa"><span itemprop="name">A. Soroa</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics</span>, </em></span><em>Seite <span itemprop="pagination">19--27</span>. </em><em>Stroudsburg, PA, USA, </em><em><span itemprop="publisher">Association for Computational Linguistics</span>, </em>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)Mon Feb 21 23:23:16 CET 2011Stroudsburg, PA, USAProceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics19--27NAACL '09A study on similarity and relatedness using distributional and WordNet-based approaches2009distributional relatedness semantic_similarity similarity wordnet This paper presents and compares WordNet-based and distributional similarity approaches. The strengths and weaknesses of each approach regarding similarity and relatedness tasks are discussed, and a combination is presented. Each of our methods independently provide the best results in their class on the RG and WordSim353 datasets, and a supervised combination of them yields the best published results on all datasets. Finally, we pioneer cross-lingual similarity, showing that our methods are easily adapted for a cross-lingual task with minor losses.A study on similarity and relatedness using distributional and WordNet-based approachesSemantic Grounding of Tag Relatedness in Social Bookmarking Systemshttps://puma.uni-kassel.de/bibtex/227198c985b3bdb6daab0f7e961b370a9/benzbenz2011-02-04T16:09:26+01:002008 grounding iswc2008 itegpub myown relatedness semantic similarity sw tag tagging tagorapub ol_web2.0 methods_concepts methods_concepthierarchy semantic_relatedness <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ciro Cattuto" itemprop="url" href="/author/Ciro%20Cattuto"><span itemprop="name">C. Cattuto</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dominik Benz" itemprop="url" href="/author/Dominik%20Benz"><span itemprop="name">D. Benz</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Hotho" itemprop="url" href="/author/Andreas%20Hotho"><span itemprop="name">A. Hotho</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerd Stumme" itemprop="url" href="/author/Gerd%20Stumme"><span itemprop="name">G. Stumme</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008</span>, </em></span><em>Volume 5318 von LNAI, </em><em>Seite <span itemprop="pagination">615--631</span>. </em><em>Heidelberg, </em><em><span itemprop="publisher">Springer</span>, </em>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:26 CET 2011HeidelbergThe Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008615--631LNAISemantic Grounding of Tag Relatedness in Social Bookmarking Systems531820082008 grounding iswc2008 itegpub myown relatedness semantic similarity sw tag tagging tagorapub ol_web2.0 methods_concepts methods_concepthierarchy semantic_relatedness Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.