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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/478/Automatic-Discovery-of-Semantic-Relations-using-MindNet"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers">
  <title><![CDATA[Information Extraction via Automatic Generation of Semantic Classifiers]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers</link>
  <description><![CDATA[Information extraction is an important unsolved problem of natural
language processing (NLP). It is the problem of extracting entities
(such as people, organizations or locations) and named relations
between entities (such as "People born-in Country") from text
documents. An important challenge in information extraction is the
labeling of training data which is usually done manually and is
therefore very expensive.

This talk introduces a new "model" to generate training data with
le...]]></description>
  <dc:date>2008-09-16</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/478/Automatic-Discovery-of-Semantic-Relations-using-MindNet">
  <title><![CDATA[Automatic Discovery of Semantic Relations using MindNet]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/478/Automatic-Discovery-of-Semantic-Relations-using-MindNet</link>
  <description><![CDATA[Information extraction deals with extracting entities (such as people,organizations or locations) and named relations between entities (such as "People born-in Country") from text documents. An important challenge in information extraction is the labeling of training data which is usually done manually and is therefore very laborious and in certain cases impractical. This paper introduces a new “model” to extract semantic relations fully automatically from text using the Encarta encyclope...]]></description>
  <dc:date>2010-05-19</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/401/Predicting-Appropriate-Semantic-Web-Terms-from-Words">
  <title><![CDATA[Predicting Appropriate Semantic Web Terms from Words]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/401/Predicting-Appropriate-Semantic-Web-Terms-from-Words</link>
  <description><![CDATA[The Semantic Web language RDF was designed to unambiguously define and use ontologies to encode data and knowledge on the Web. Many people find it difficult, however, to write complex RDF statements and queries because doing so requires familiarity with the appropriate ontologies and the terms they define. We describe a system that suggests appropriate RDF terms given semantically related English words and general domain and context information. We use the Swoogle Semantic Web search engine t...]]></description>
  <dc:date>2008-07-13</dc:date>
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