PUMA publications for /user/iteg/taghttps://puma.uni-kassel.de/user/iteg/tagPUMA RSS feed for /user/iteg/tag2024-03-29T16:49:42+01:00A Comparison of content-based Tag Recommendations in Folksonomy Systemshttps://puma.uni-kassel.de/bibtex/20a4a7f95efa9493d804816bb75ecbf33/itegiteg2011-11-22T10:26:32+01:002011 content folksonomy itegpub l3s myown recommendations recommender tag tagorapub <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Illig" itemprop="url" href="/author/Jens%20Illig"><span itemprop="name">J. Illig</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>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert Jäschke" itemprop="url" href="/author/Robert%20J%c3%a4schke"><span itemprop="name">R. Jäschke</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">Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)</span>, </em></span><em><span itemprop="publisher">Springer</span>, </em>(<em><span>2011<meta content="2011" itemprop="datePublished"/></span></em>)Tue Nov 22 10:26:32 CET 2011Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)A Comparison of content-based Tag Recommendations in Folksonomy Systems20112011 content folksonomy itegpub l3s myown recommendations recommender tag tagorapub Tag Recommendations in Social Bookmarking Systemshttps://puma.uni-kassel.de/bibtex/2955bcf14f3272ba6eaf3dadbef6c0b10/itegiteg2011-11-22T10:26:32+01:002.0 2008 Recommendations bookmarking itegpub logsonomies myown recommendations recommender social systems tag tagorapub tags web web2.0 web20 <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert Jäschke" itemprop="url" href="/author/Robert%20J%c3%a4schke"><span itemprop="name">R. Jäschke</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Leandro Marinho" itemprop="url" href="/author/Leandro%20Marinho"><span itemprop="name">L. Marinho</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>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lars Schmidt-Thieme" itemprop="url" href="/author/Lars%20Schmidt-Thieme"><span itemprop="name">L. Schmidt-Thieme</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/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>AI Communications</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">21 </span></span>(<span itemprop="issueNumber">4</span>):
<span itemprop="pagination">231-247</span></em> </span>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Tue Nov 22 10:26:32 CET 2011AmsterdamAI Communications4231-247Tag Recommendations in Social Bookmarking Systems2120082.0 2008 Recommendations bookmarking itegpub logsonomies myown recommendations recommender social systems tag tagorapub tags web web2.0 web20 Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of
user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
Semantic Grounding of Tag Relatedness in Social Bookmarking Systemshttps://puma.uni-kassel.de/bibtex/227198c985b3bdb6daab0f7e961b370a9/itegiteg2011-11-22T10:26:32+01:002008 grounding iswc2008 itegpub methods_concepthierarchy methods_concepts myown ol_web2.0 relatedness semantic semantic_relatedness similarity sw tag tagging tagorapub <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>)Tue Nov 22 10:26:32 CET 2011HeidelbergThe Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008615--631LNAISemantic Grounding of Tag Relatedness in Social Bookmarking Systems531820082008 grounding iswc2008 itegpub methods_concepthierarchy methods_concepts myown ol_web2.0 relatedness semantic semantic_relatedness similarity sw tag tagging tagorapub 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.