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 <channel rdf:about="http://ebiquity.umbc.edu/tag/knowledge base/">
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  <image rdf:resource="http://ebiquity.umbc.edu/img/logo.jpg" />  <title><![CDATA[RSS Tag Search]]></title>
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  <description><![CDATA[RSS Tag Search]]></description>
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    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/535/Creating-and-Exploiting-a-Hybrid-Knowledge-Base-for-Linked-Data"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/492/Entity-Disambiguation-for-Knowledge-Base-Population"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/482/HLTCOE-Approaches-to-Knowledge-Base-Population-at-TAC-2009"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/354/Wikitology-A-Novel-Hybrid-Knowledge-Base-Derived-from-Wikipedia"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation"/>
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 <image rdf:about="http://ebiquity.umbc.edu/img/logo.jpg">
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 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/535/Creating-and-Exploiting-a-Hybrid-Knowledge-Base-for-Linked-Data">
  <title><![CDATA[Creating and Exploiting a Hybrid Knowledge Base for Linked Data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/535/Creating-and-Exploiting-a-Hybrid-Knowledge-Base-for-Linked-Data</link>
  <description><![CDATA[Twenty years ago Tim Berners-Lee proposed a distributed hypertext system based on standard Internet protocols. The Web that resulted fundamentally changed the ways we share information and services, both on the public Internet and within organizations. That original proposal contained the seeds of another effort that has not yet fully blossomed: a Semantic Web designed to enable computer programs to share and understand structured and semi-structured information easily. We will review the evo...]]></description>
  <dc:date>2011-04-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/492/Entity-Disambiguation-for-Knowledge-Base-Population">
  <title><![CDATA[Entity Disambiguation for Knowledge Base Population]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/492/Entity-Disambiguation-for-Knowledge-Base-Population</link>
  <description><![CDATA[The integration of facts derived from information extraction systems into existing knowledge bases requires a system to disambiguate entity mentions in the text. This is challenging due to issues such as non-uniform variations in entity names, mention ambiguity, and entities absent from a knowledge base. We present a state of the art system for entity disambiguation that not only addresses these challenges but also scales to knowledge bases with several million entries using very little resou...]]></description>
  <dc:date>2010-08-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/482/HLTCOE-Approaches-to-Knowledge-Base-Population-at-TAC-2009">
  <title><![CDATA[HLTCOE Approaches to Knowledge Base Population at TAC 2009]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/482/HLTCOE-Approaches-to-Knowledge-Base-Population-at-TAC-2009</link>
  <description><![CDATA[The HLTCOE participated in the entity linking and slot filling tasks at TAC 2009. A machine learning-based approach to entity linking, operating over a wide range of feature types, yielded good performance on the entity linking task. Slot-filling based on sentence selection, application of weak patterns and exploitation of redundancy was ineffective in the slot filling task.]]></description>
  <dc:date>2009-11-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery">
  <title><![CDATA[Knowledge Base Evaluation for Semantic Knowledge Discovery]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery</link>
  <description><![CDATA[Semantic knowledge discovery has traditionally been evaluated at the text level. For example, evaluations such as MUC and ACE evaluate the information extraction of particular types of semantic roles and relations primarily at the mention level. We suggest that evaluating at the level of a knowledge base (KB) extracted from the text has significant advantages over evaluation at the text level. By knowledge base, we mean the combination of a database, a descriptive schema for the contents of t...]]></description>
  <dc:date>2008-11-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/354/Wikitology-A-Novel-Hybrid-Knowledge-Base-Derived-from-Wikipedia">
  <title><![CDATA[Wikitology: A Novel Hybrid Knowledge Base Derived from Wikipedia]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/354/Wikitology-A-Novel-Hybrid-Knowledge-Base-Derived-from-Wikipedia</link>
  <description><![CDATA[PhD Defense

World knowledge may be available in different forms such as
relational databases, triple stores, link graphs, meta-data and
free text. Human minds are capable of understanding and
reasoning over knowledge represented in different ways and are
influenced by social, contextual and environmental factors. By
following a similar model, we have integrated a variety of
knowledge sources in a novel way to produce a single hybrid
knowledge base, Wikitology, enabling applications ...]]></description>
  <dc:date>2010-07-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation">
  <title><![CDATA[Generic knowledge: acquisition and representation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation</link>
  <description><![CDATA[AI is beginning to make some dents in the "knowledge acquisition bottleneck", the problem of acquiring large amounts of general world knowledge to support language understanding and commonsense reasoning. Two text-based approaches to the problem are (1) to abstract such knowledge from patterns of predication and modification in miscellaneous texts, and (2) to derive such knowledge by direct interpretation of general statements in ordinary language, such as are found in lexicons and resources ...]]></description>
  <dc:date>2009-10-06</dc:date>
 </item>
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