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	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=unsupervised+learning">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=unsupervised+learning]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for unsupervised learning]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/155/A-Trust-Based-Framework-for-Secure-Data-Aggregation-in-Wireless-Sensor-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/633/Online-unsupervised-coreference-resolution-for-semi-structured-heterogeneous-data"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue">
  <title><![CDATA[Is your personal data at risk? App analytics to the rescue]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue</link>
  <description><![CDATA[According to Virustotal, a prominent virus and malware tool, the Google Play Store has a few thousand apps from major malware families. Given such a revelation, access control systems for mobile data management, have reached a state of critical importance. We propose the development of a system which would help us detect the pathways using which user's data is being stolen from their mobile devices. We use a multi layered approach which includes app meta data analysis, understanding code patt...]]></description>
  <dc:date>2015-09-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/155/A-Trust-Based-Framework-for-Secure-Data-Aggregation-in-Wireless-Sensor-Networks">
  <title><![CDATA[A Trust Based Framework for Secure Data Aggregation in Wireless Sensor Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/155/A-Trust-Based-Framework-for-Secure-Data-Aggregation-in-Wireless-Sensor-Networks</link>
  <description><![CDATA[In unattended and hostile environments, node compromise can
become a disastrous threat to wireless sensor networks and
introduce uncertainty in the aggregation results. A compromise
node often tends to completely reveal its secrets to an adversary
which in turn renders purely cryptography-based approaches
vulnerable. How to secure the information aggregation process
against node compromise attacks and quantify the uncertainty in
the aggregation results has become an important research...]]></description>
  <dc:date>2006-05-10</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/633/Online-unsupervised-coreference-resolution-for-semi-structured-heterogeneous-data">
  <title><![CDATA[Online unsupervised coreference resolution for semi-structured heterogeneous data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/633/Online-unsupervised-coreference-resolution-for-semi-structured-heterogeneous-data</link>
  <description><![CDATA[A pair of RDF instances are said to corefer when they are intended to denote the same
thing in the world, for example, when two nodes of type foaf:Person describe the same
individual. This problem is central to integrating and inter-linking semi-structured
datasets. We are developing an online, unsupervised coreference resolution framework
for heterogeneous, semi-structured data. The online aspect requires us to process
new instances as they appear and not as a batch. The instances are h...]]></description>
  <dc:date>2012-11-30</dc:date>
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