PUMA publications for /user/stephandoerfel/recommender%20folksonomyhttps://puma.uni-kassel.de/user/stephandoerfel/recommender%20folksonomyPUMA RSS feed for /user/stephandoerfel/recommender%20folksonomy2024-03-28T20:00:57+01:00Factor Models for Tag Recommendation in BibSonomyhttps://puma.uni-kassel.de/bibtex/2ceed045a84e121fa37384f797306d30f/stephandoerfelstephandoerfel2010-11-08T12:05:22+01:003d folksonomy kde recommender social tensor <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Rendle" itemprop="url" href="/author/Steffen%20Rendle"><span itemprop="name">S. Rendle</span></a></span>, и <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>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">ECML PKDD Discovery Challenge 2009 (DC09)</span>, </em></span><em> 497, </em><em>стр. <span itemprop="pagination">235--242</span>. </em><em>Bled, Slovenia, </em><em><span itemprop="publisher">CEUR Workshop Proceedings</span>, </em>(<em><span>Сентябрь 2009<meta content="Сентябрь 2009" itemprop="datePublished"/></span></em>)Mon Nov 08 12:05:22 CET 2010Bled, SloveniaECML PKDD Discovery Challenge 2009 (DC09)September235--242Factor Models for Tag Recommendation in BibSonomy49720093d folksonomy kde recommender social tensor This paper describes our approach to the ECML/PKDD Discovery Challenge 2009. Our approach is a pure statistical model taking no content information into account. It tries to find latent interactions between users, items and tags by factorizing the observed tagging data. The factorization model is learned by the Bayesian Personal Ranking method (BPR) which is inspired by a Bayesian analysis of personalized ranking with missing data. To prevent overfitting, we ensemble the models over several iterations and hyperparameters. Finally, we enhance the top-n lists by estimating how many tags to recommend.Testing and Evaluating Tag Recommenders in a Live Systemhttps://puma.uni-kassel.de/bibtex/21320904b208d53bd5d49e751cbfcc268/stephandoerfelstephandoerfel2009-09-04T16:47:44+02:002009 BibSonomy conference folksonomy framework recommender <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="Folke Eisterlehner" itemprop="url" href="/author/Folke%20Eisterlehner"><span itemprop="name">F. Eisterlehner</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>, и <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">RecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems</span>, </em></span><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)<em>(to appear).</em>Fri Sep 04 16:47:44 CEST 2009New York, NY, USARecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems(to appear)Testing and Evaluating Tag Recommenders in a Live System20092009 BibSonomy conference folksonomy framework recommender The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on the evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents a �rst evaluation of two exemplarily deployed recommendation methods.tag-recommender für acm09