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  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.
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  <pub:InProceedings rdf:about="http://ebiquity.umbc.edu/paper/html/id/92/A-Probabilistic-Extension-to-Ontology-Language-OWL">
    <rdfs:label><![CDATA[A Probabilistic Extension to Ontology Language OWL]]></rdfs:label>
    <pub:title><![CDATA[A Probabilistic Extension to Ontology Language OWL]]></pub:title>
    <pub:publishedOn rdf:datatype="&xsd;dateTime">2004-01-05T00:00:00-05:00</pub:publishedOn>
    <pub:abstract><![CDATA[To support uncertain ontology representation and ontology
reasoning and mapping, we propose to incorporate
Bayesian networks (BN), a widely used graphic model
for knowledge representation under uncertainty and OWL,
the de facto industry standard ontology language recommended
by W3C. First, OWL is augmented to allow
additional probabilistic markups, so probabilities can be
attached with individual concepts and properties in an
OWL ontology. Secondly, a set of translation rules is
defined to convert this probabilistically annotated OWL
ontology into the directed acyclic graph (DAG) of a BN.
Finally, the BN is completed by constructing conditional
probability tables (CPT) for each node in the DAG. Our
probabilistic extension to OWL is consistent with OWL
semantics, and the translated BN is associated with a
joint probability distribution over the application domain.
General Bayesian network inference procedures (e.g., belief
propagation or junction tree) can be used to compute
P(C|e): the degree of the overlap or inclusion between
a concept C and a concept represented by a description
e. We also provide a similarity measure that can be used
to find the most similar concept that a given description
belongs to.]]></pub:abstract>
    <pub:pages><![CDATA[10]]></pub:pages>
    <pub:address><![CDATA[Big Island, Hawaii]]></pub:address>
    <pub:counter>1635</pub:counter>
    <pub:googleKey>LlPgNwT86xcJ</pub:googleKey>
    <pub:googleCitations>93</pub:googleCitations>
    <pub:tag><![CDATA[bayesian reasoning]]></pub:tag>
    <pub:tag><![CDATA[uncertainty]]></pub:tag>
    <pub:tag><![CDATA[semantic web]]></pub:tag>
    <pub:tag><![CDATA[owl]]></pub:tag>
    <pub:booktitle><![CDATA[Proceedings of the 37th  Hawaii International Conference On System Sciences (HICSS-37).]]></pub:booktitle>
    <pub:author>
       <rdf:List>
         <rdf:first><person:PhDAlumnus rdf:about="http://ebiquity.umbc.edu/person/html/Zhongli/Ding/"><person:name><![CDATA[Zhongli  Ding]]></person:name><rdfs:label><![CDATA[Zhongli  Ding]]></rdfs:label></person:PhDAlumnus></rdf:first>
         <rdf:rest>
           <rdf:List>
             <rdf:first><person:PrincipalFaculty rdf:about="http://ebiquity.umbc.edu/person/html/Yun/Peng/"><person:name><![CDATA[Yun  Peng]]></person:name><rdfs:label><![CDATA[Yun  Peng]]></rdfs:label></person:PrincipalFaculty></rdf:first>
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    </pub:author>
    <pub:firstAuthor><person:PhDAlumnus rdf:about="http://ebiquity.umbc.edu/person/html/Zhongli/Ding/"><person:name><![CDATA[Zhongli  Ding]]></person:name><rdfs:label><![CDATA[Zhongli  Ding]]></rdfs:label></person:PhDAlumnus></pub:firstAuthor>
    <pub:relatedProject><project:PastProject rdf:about="http://ebiquity.umbc.edu/project/html/id/59/Bayes-OWL"><project:title><![CDATA[Bayes OWL]]></project:title><rdfs:label><![CDATA[Bayes OWL]]></rdfs:label></project:PastProject></pub:relatedProject>
    <pub:softCopy><pub:SoftCopy>
      <pub:softCopyFormat><![CDATA[PDF Document]]></pub:softCopyFormat>
      <pub:softCopyURI><![CDATA[http://ebiquity.umbc.edu/get/a/publication/81.pdf]]></pub:softCopyURI>
      <pub:softCopySize>140036</pub:softCopySize>
    </pub:SoftCopy></pub:softCopy>
  </pub:InProceedings>

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