<?xml version="1.0" encoding="UTF-8" ?>
<rdf:RDF
 xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
 xmlns="http://purl.org/rss/1.0/"
 xmlns:dc="http://purl.org/dc/elements/1.1/"
 xmlns:cc="http://web.resource.org/cc/"
 >
<!--
  This ontology document is licensed under the Creative Commons
  Attribution License. To view a copy of this license, visit
  http://creativecommons.org/licenses/by/2.0/ or send a letter to
  Creative Commons, 559 Nathan Abbott Way, Stanford, California
  94305, USA.
-->
 <channel rdf:about="http://ebiquity.umbc.edu/tag/folksonomy/">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <image rdf:resource="http://ebiquity.umbc.edu/img/logo.jpg" />  <title><![CDATA[RSS Tag Search]]></title>
  <link>http://ebiquity.umbc.edu/tag/folksonomy/</link>
  <description><![CDATA[RSS Tag Search]]></description>
  <items>
   <rdf:Seq>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomies"/>
   </rdf:Seq>
  </items>
 </channel>
 <image rdf:about="http://ebiquity.umbc.edu/img/logo.jpg">
  <title>UMBC ebiquity research group</title>
  <link>http://ebiquity.umbc.edu</link>
  <url>http://ebiquity.umbc.edu/img/logo.jpg</url>
 </image>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomies">
  <title><![CDATA[Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomies</link>
  <description><![CDATA[We present a simple technique for detecting communities by utilizing both the link structure and folksonomy (or tag) information that is readily available in most social media systems. A simple way to describe our approach is by defining a community as a set of nodes in a graph that link more frequently to within this set than outside it and they share similar tags. Our technique is based on the Normalized Cut (NCut) algorithm and can be easily and efficiently implemented. We validate our met...]]></description>
  <dc:date>2008-08-24</dc:date>
 </item>
</rdf:RDF>
