<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0" xml:base="https://www.dbdump.org"  xmlns:dc="http://purl.org/dc/elements/1.1/">
<channel>
 <title>dbdump.org - wikipedia</title>
 <link>https://www.dbdump.org/taxonomy/term/22</link>
 <description></description>
 <language>en</language>
<item>
 <title>Creating specialized ontologies using Wikipedia: The Muninn Experience.</title>
 <link>https://www.dbdump.org/news/2012/06/presentation-at-wikipedia-academy-creating-specialized-ontologies-using-wikipedia---the-muninn-exper.html</link>
 <description>&lt;div class=&quot;field field-name-body field-type-text-with-summary field-label-hidden&quot;&gt;&lt;div class=&quot;field-items&quot;&gt;&lt;div class=&quot;field-item even&quot; property=&quot;content:encoded&quot;&gt;&lt;p&gt;&lt;img alt=&quot;Wiki.png&quot; class=&quot;mt-image-left&quot; height=&quot;134&quot; src=&quot;http://www.dbdump.org/news/assets_c/2012/06/Wiki-thumb-119x134-57.png&quot; style=&quot;float: left; margin: 0 20px 20px 0;&quot; width=&quot;119&quot; /&gt;&lt;/p&gt;
&lt;div&gt;
	Creating specialized ontologies using Wikipedia: The &lt;a href=&quot;http://www.muninn-project.org/&quot;&gt;Muninn&lt;/a&gt; Experience.&lt;/div&gt;
&lt;div&gt;
	&lt;a href=&quot;http://wikipedia-academy.de/2012/wiki/Main_Page&quot;&gt;Wikipedia Academy 2012&lt;/a&gt;&lt;/div&gt;
&lt;div&gt;
	&lt;a href=&quot;http://wikipedia-academy.de/2012/wiki/Schedule#Paper_Session_III:_Analysing_Wikipedia_Article_Data&quot;&gt;Paper Session III&lt;/a&gt;, Saturday June 30, 10:30-11:30&lt;/div&gt;
&lt;div&gt;
	 &lt;/div&gt;
&lt;div&gt;
	Abstract:&lt;/div&gt;
&lt;div&gt;
	This paper reports on the experiences of the Muninn project in creating specialized ontologies for historical governmental and military organizations using the Wikipedia data set and its linked open data companion DBpedia.  The motivation for the ontologies and the extraction methods used are explained and their performances reviewed.  Overall Wikipedia is a very accurate knowledge base from which multilingual concepts can be extracted.  The caveat is that while the information is almost always present, it is not always straightforward to retrieve because of missing structures or categorization information. Hence, an iterative methodology has been found to work best in extracting information from Wikipedia.&lt;/div&gt;
&lt;!--break--&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;form-item form-type-item&quot;&gt;
  &lt;label&gt;Language &lt;/label&gt;
 Undefined
&lt;/div&gt;
&lt;div class=&quot;field field-name-field-tags field-type-taxonomy-term-reference field-label-above&quot;&gt;&lt;div class=&quot;field-label&quot;&gt;Tags:&amp;nbsp;&lt;/div&gt;&lt;div class=&quot;field-items&quot;&gt;&lt;div class=&quot;field-item even&quot; rel=&quot;dc:subject&quot;&gt;&lt;a href=&quot;/taxonomy/term/21&quot; typeof=&quot;skos:Concept&quot; property=&quot;rdfs:label skos:prefLabel&quot; datatype=&quot;&quot;&gt;ontologies&lt;/a&gt;&lt;/div&gt;&lt;div class=&quot;field-item odd&quot; rel=&quot;dc:subject&quot;&gt;&lt;a href=&quot;/taxonomy/term/13&quot; typeof=&quot;skos:Concept&quot; property=&quot;rdfs:label skos:prefLabel&quot; datatype=&quot;&quot;&gt;lod&lt;/a&gt;&lt;/div&gt;&lt;div class=&quot;field-item even&quot; rel=&quot;dc:subject&quot;&gt;&lt;a href=&quot;/taxonomy/term/22&quot; typeof=&quot;skos:Concept&quot; property=&quot;rdfs:label skos:prefLabel&quot; datatype=&quot;&quot;&gt;wikipedia&lt;/a&gt;&lt;/div&gt;&lt;div class=&quot;field-item odd&quot; rel=&quot;dc:subject&quot;&gt;&lt;a href=&quot;/taxonomy/term/23&quot; typeof=&quot;skos:Concept&quot; property=&quot;rdfs:label skos:prefLabel&quot; datatype=&quot;&quot;&gt;dbpedia&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</description>
 <pubDate>Mon, 25 Jun 2012 21:10:00 +0000</pubDate>
 <dc:creator>warren</dc:creator>
 <guid isPermaLink="false">18 at https://www.dbdump.org</guid>
 <comments>https://www.dbdump.org/news/2012/06/presentation-at-wikipedia-academy-creating-specialized-ontologies-using-wikipedia---the-muninn-exper.html#comments</comments>
</item>
</channel>
</rss>
