PUMA publications for /author/Pearl%20Puhttps://puma.uni-kassel.de/author/Pearl%20PuPUMA RSS feed for /author/Pearl%20Pu2024-03-28T21:52:58+01:00Interaction design guidelines on critiquing-based recommender systemshttps://puma.uni-kassel.de/bibtex/2f0e063a97473519ca650fe029da73ce7/jaeschkejaeschke2012-12-13T10:31:05+01:00stair critiquing recommender interaction <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Li Chen" itemprop="url" href="/author/Li%20Chen"><span itemprop="name">L. Chen</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pearl Pu" itemprop="url" href="/author/Pearl%20Pu"><span itemprop="name">P. Pu</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>User Modeling and User-Adapted Interaction</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">19 </span></span>(<span itemprop="issueNumber">3</span>):
<span itemprop="pagination">167--206</span></em> </span>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)Thu Dec 13 10:31:05 CET 2012User Modeling and User-Adapted Interaction3167--206Interaction design guidelines on critiquing-based recommender systems192009stair critiquing recommender interaction A critiquing-based recommender system acts like an artificial salesperson. It engages users in a conversational dialog where users can provide feedback in the form of critiques to the sample items that were shown to them. The feedback, in turn, enables the system to refine its understanding of the user’s preferences and prediction of what the user truly wants. The system is then able to recommend products that may better stimulate the user’s interest in the next interaction cycle. In this paper, we report our extensive investigation of comparing various approaches in devising critiquing opportunities designed in these recommender systems. More specifically, we have investigated two major design elements which are necessary for a critiquing-based recommender system: