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<biblioentry xreflabel="ISBN:3540345191" id="ISBN:3540345191">
   <authorgroup>

   </authorgroup>
<citetitle pubwork="article">Enabling Semantic Web Services: The Web Service Modeling Ontology</citetitle>

   <publisher>
      <publishername>Springer&#45;Verlag</publishername>
   </publisher>



   <pubdate>2006</pubdate>  

</biblioentry>
<biblioentry xreflabel="Hepp:2006:HWC" id="Hepp:2006:HWC">
   <authorgroup>
       <author><firstname>Hepp&#44;</firstname><surname>Martin</surname></author>
       <author><firstname>Bachlechner&#44;</firstname><surname>Daniel</surname></author>
       <author><firstname>Siorpaes&#44;</firstname><surname>Katharina</surname></author> 
   </authorgroup>
<citetitle pubwork="article">Harvesting Wiki Consensus &#45; Using Wikipedia Entries as Ontology Elements</citetitle>

   <publisher>
      <publishername>ESWC2006</publishername>
   </publisher>



   <pubdate>2006</pubdate>  
   <abstract>
      <para>One major obstacle towards adding machine&#45;readable annotation to&#13;&#10;&#9;&#13;&#10;&#9; existing Web content is the lack of domain ontologies. While FOAF&#13;&#10;&#9;and Dublin&#13;&#10;&#9;&#13;&#10;&#9; Core are popular means for expressing relationships between Web resources&#13;&#10;&#9;&#13;&#10;&#9; and between Web resources and literal values&#44; we widely lack unique&#13;&#10;&#9;identifiers&#13;&#10;&#9;&#13;&#10;&#9; for common concepts and instances. Also&#44; most available ontologies&#13;&#10;&#9;have a&#13;&#10;&#9;&#13;&#10;&#9; very weak community grounding in the sense that they are designed&#13;&#10;&#9;by single&#13;&#10;&#9;&#13;&#10;&#9; individuals or small groups of individuals&#44; while the majority of&#13;&#10;&#9;potential users&#13;&#10;&#9;&#13;&#10;&#9; is not involved in the process of proposing new ontology elements&#13;&#10;&#9;or achieving&#13;&#10;&#9;&#13;&#10;&#9; consensus. This is in sharp contrast to natural language where the&#13;&#10;&#9;evolution of&#13;&#10;&#9;&#13;&#10;&#9; the vocabulary is under the control of the user community. At the&#13;&#10;&#9;same time&#44;&#13;&#10;&#9;&#13;&#10;&#9; we can observe that&#44; within Wiki communities&#44; especially Wikipedia&#44;&#13;&#10;&#9;a large&#13;&#10;&#9;&#13;&#10;&#9; number of users is able to create comprehensive domain representations&#13;&#10;&#9;in the&#13;&#10;&#9;&#13;&#10;&#9; sense of unique&#44; machine&#45;feasible&#44; identifiers and concept definitions&#13;&#10;&#9;which are&#13;&#10;&#9;&#13;&#10;&#9; sufficient for humans to grasp the intension of the concepts. The&#13;&#10;&#9;English&#13;&#10;&#9;&#13;&#10;&#9; version of Wikipedia contains now more than one million entries and&#13;&#10;&#9;thus the&#13;&#10;&#9;&#13;&#10;&#9; same amount of URIs plus a human&#45;readable description. While this&#13;&#10;&#9;collection&#13;&#10;&#9;&#13;&#10;&#9; is on the lower end of ontology expressiveness&#44; it is likely the&#13;&#10;&#9;largest living&#13;&#10;&#9;&#13;&#10;&#9; ontology that is available today. In this paper&#44; we (1) show that&#13;&#10;&#9;standard Wiki&#13;&#10;&#9;&#13;&#10;&#9; technology can be easily used as an ontology development environment&#13;&#10;&#9;for&#13;&#10;&#9;&#13;&#10;&#9; named classes&#44; reducing entry barriers for the participation of users&#13;&#10;&#9;in the&#13;&#10;&#9;&#13;&#10;&#9; creation and maintenance of lightweight ontologies&#44; (2) prove that&#13;&#10;&#9;the URIs of&#13;&#10;&#9;&#13;&#10;&#9; Wikipedia entries are surprisingly reliable identifiers for ontology&#13;&#10;&#9;concepts&#44; and&#13;&#10;&#9;&#13;&#10;&#9; (3) demonstrate the applicability of our approach in a use case.
      </para>
   </abstract>
</biblioentry>
<biblioentry xreflabel="tx_deriinproceedings_list_uid142" id="tx_deriinproceedings_list_uid142">
   <authorgroup>
       <author><firstname>Hepp&#44;</firstname><surname>Martin</surname></author>
       <author><firstname>Siorpaes&#44;</firstname><surname>Katharina</surname></author>
       <author><firstname>Bachlechner&#44;</firstname><surname>Daniel</surname></author> 
   </authorgroup>
<citetitle pubwork="article">Towards the Semantic Web in e&#45;Tourism: Lack of Semantics or Lack of Content&#63;</citetitle>





   <pubdate>2006</pubdate>  

</biblioentry>
<biblioentry xreflabel="conf/gi/HothoJSS06" id="conf/gi/HothoJSS06">
   <authorgroup>
       <author><firstname>Hotho&#44;</firstname><surname>Andreas</surname></author>
       <author><firstname>J&#228;schke&#44;</firstname><surname>Robert</surname></author>
       <author><firstname>Schmitz&#44;</firstname><surname>Christoph</surname></author>
       <author><firstname>Stumme&#44;</firstname><surname>Gerd</surname></author> 
   </authorgroup>
<citetitle pubwork="article">Emergent Semantics in BibSonomy.</citetitle>

   <publisher>
      <publishername>GI</publishername>
   </publisher>
   <volumenum>94</volumenum> 

   <artpagenums>305-312</artpagenums> 
   <pubdate>2006</pubdate>  

</biblioentry>
<biblioentry xreflabel="lambiotte05tripartite" id="lambiotte05tripartite">
   <authorgroup>
       <author><firstname>Lambiotte&#44;</firstname><surname>R.</surname></author>
       <author><firstname>Ausloos&#44;</firstname><surname>M.</surname></author> 
   </authorgroup>
<citetitle pubwork="article">Collaborative tagging as a tripartite network</citetitle>
   <citetitle pubwork="journal">Lecture Notes in Computer Science</citetitle>



   <artpagenums>1114 - 1117</artpagenums> 
   <pubdate>2006</pubdate>  
   <abstract>
      <para>We describe online collaborative communities by tripartite networks&#44; the nodes being persons&#44; items and tags. We introduce projection methods in order to uncover the structures of the networks&#44; i.e. communities of users&#44; genre families... &lt;br /&gt;To do so&#44; we focus on the correlations between the nodes&#44; depending on their profiles&#44; and use percolation techniques that consist in removing less correlated links and observing the shaping of disconnected islands. The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.
      </para>
   </abstract>
</biblioentry>
<biblioentry xreflabel="Schmitz_et_al_2006" id="Schmitz_et_al_2006">
   <authorgroup>
       <author><firstname>Schmitz&#44;</firstname><surname>Christoph</surname></author>
       <author><firstname>Hotho&#44;</firstname><surname>Andreas</surname></author>
       <author><firstname>J&#228;schke&#44;</firstname><surname>Robert</surname></author>
       <author><firstname>Stumme&#44;</firstname><surname>Gerd</surname></author> 
   </authorgroup>
<citetitle pubwork="article">Mining Association Rules in Folksonomies</citetitle>

   <publisher>
      <publishername>Springer</publishername>
   </publisher>


   <artpagenums>261&#x2013;270</artpagenums> 
   <pubdate>2006</pubdate>  
   <abstract>
      <para>Social bookmark tools are rapidly emerging on the Web. In such&#13;&#10;systems users are setting up lightweight conceptual structures&#13;&#10;called folksonomies. These systems provide currently relatively few&#13;&#10;structure. We discuss in this paper&#44; how association rule mining&#13;&#10;can be adopted to analyze and structure folksonomies&#44; and how the results can be used&#13;&#10;for ontology learning and supporting emergent semantics. We&#13;&#10;demonstrate our approach on a large scale dataset stemming from an&#13;&#10;online system.
      </para>
   </abstract>
</biblioentry>
</bibliography>

