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 <channel rdf:about="http://ebiquity.umbc.edu/tag/classification/">
  <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/classification/</link>
  <description><![CDATA[RSS Tag Search]]></description>
  <items>
   <rdf:Seq>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/554/Clinical-Genomic-Analysis-for-Disease-Prediction"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/377/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/244/Wikipedia-as-an-ontology"/>
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 <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>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/554/Clinical-Genomic-Analysis-for-Disease-Prediction">
  <title><![CDATA[Clinical-Genomic Analysis for Disease Prediction]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/554/Clinical-Genomic-Analysis-for-Disease-Prediction</link>
  <description><![CDATA[Recent advances in genomic research have generated vast amounts of information that can help identify individuals who differ in their susceptibility to a particular disease or response to a specific treatment. This information may offer solutions for the treatment of complex chronic diseases that are influenced by a wide array of factors. This vast amount of information brings critical challenges in applying advanced technology to synthesize clinical-genomic patient data. Synthesizing this in...]]></description>
  <dc:date>2011-07-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/377/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web">
  <title><![CDATA[Learning the Semantic Meaning of a Concept from the Web]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/377/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web</link>
  <description><![CDATA[Many researchers have used text classification method in solving the ontology mapping problem. Their mapping results heavily depend on the availability of quality exemplars used as training data. However, manual preparation of exemplars is costly. In this work, we propose to automatically extract text from web pages returned by a search engine. Search queries are formed according to the semantic information given in the ontology. We have implemented a prototype system that automates the entir...]]></description>
  <dc:date>2007-05-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/244/Wikipedia-as-an-ontology">
  <title><![CDATA[Wikipedia as an ontology]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/244/Wikipedia-as-an-ontology</link>
  <description><![CDATA[Identifying the topics and concepts associated with a document
or collection of documents is a common task for many
applications. It can help in the annotation and categorization
of documents in a corpus. Knowing the topics of documents a
user has selected and viewed on the Web or from a collection
can be used to model the user's current topical interests for
improving search results, business intelligence or selecting
appropriate advertisements.

We are exploring the idea of using W...]]></description>
  <dc:date>2007-10-01</dc:date>
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