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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/249/A-Bayesian-Network-Approach-to-Ontology-Mapping">
  <title><![CDATA[A Bayesian Network Approach to Ontology Mapping]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/249/A-Bayesian-Network-Approach-to-Ontology-Mapping</link>
  <description><![CDATA[This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BN. Probabilities needed for constructing conditional probability tables (CPT...]]></description>
  <dc:date>2005-11-06</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/235/A-Bayesian-Methodology-towards-Automatic-Ontology-Mapping">
  <title><![CDATA[A Bayesian Methodology towards Automatic Ontology Mapping]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/235/A-Bayesian-Methodology-towards-Automatic-Ontology-Mapping</link>
  <description><![CDATA[This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. The pro-posed method includes four components: 1) learning prob-abilities (priors about concepts, conditionals between sub-concepts and superconcepts, and raw semantic similarities between concepts in two different ontologies) using Naive Bayes text classification technique, by explicitl...]]></description>
  <dc:date>2005-07-09</dc:date>
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  <title><![CDATA[A Tool For Mapping Between Two Ontologies Using Explicit Information]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/110/A-Tool-For-Mapping-Between-Two-Ontologies-Using-Explicit-Information</link>
  <dc:date>2002-07-07</dc:date>
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 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/283/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies">
  <title><![CDATA[A Schema-Based Approach Combined with Inter-Ontology Reasoning to Construct Consensus Ontologies]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/283/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies</link>
  <description><![CDATA[As the Semantic Web gains attention as the next generation of the Web, the issue of reconciling different views of independently developed and exposed data sources becomes increasingly important. Ontology integration serves as a basis for solving this problem. In this paper, we describe an approach to construct a consensus ontology from numerous, independently designed ontologies.

Our method has the following features: i) the matching is carried out at the schema level; ii) the alignment o...]]></description>
  <dc:date>2009-11-09</dc:date>
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  <title><![CDATA[Semantically-Linked Bayesian Networks]]></title>
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  <description><![CDATA[At the present time, Bayesian networks (BNs), presumably the most popular uncertainty inference framework, are still widely used as standalone systems. When the problem itself is distributed, domain knowledge has to be centralized and unified before a single BN can be created. Alternatively, separate BNs describing related sub-domains or different aspects of the same domain may be created, but it is difficult to combine them for problem solving even if the interdependent relations between var...]]></description>
  <dc:date>2006-08-02</dc:date>
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  <title><![CDATA[Learning the Semantic Meaning of a Concept from the Web]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/166/Learning-the-Semantic-Meaning-of-a-Concept-from-the-Web</link>
  <description><![CDATA[Many researchers have applied text classification techniques to the ontology mapping problem. The mapping results in these researches heavily depend on the availability of highly relevant text exemplars associated with individual concepts. However, manual preparation of exemplars is costly. In this work, we propose to automatically collect text exemplars by downloading and processing web pages listed in the search results obtained by querying a search engine. Search queries are formed for eac...]]></description>
  <dc:date>2006-08-03</dc:date>
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