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|Month=September
 
|Month=September
 
|Booktitle=Working Notes of the CLEF 2010 Lab Sessions
 
|Booktitle=Working Notes of the CLEF 2010 Lab Sessions
|Publisher=Notebook Papers
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|Publisher=CLEF 2010
 
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{{Publikation Details
 
{{Publikation Details
|Abstract=Most Information Retrieval models take documents as Bag- of-Words and are thereby bound to the language of the documents. In this paper, we present an approach using Linked Open Data re- sources, i.e. URIs, as interlingual document representations. Documents and queries are summarized by the resources they contain. We show the applicability of our approach for multilingual retrieval with a case study on expert search.
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|Abstract=Most Information Retrieval models take documents as Bag-of-Words and are thereby bound to the language of the documents. In this paper, we present an approach using Linked Open Data resources, i.e. URIs, as interlingual document representations. Documents and queries are summarized by the resources they contain. We show the applicability of our approach for multilingual retrieval with a case study on expert search.
 
|ISBN=978-88-904810-0-0
 
|ISBN=978-88-904810-0-0
 
|ISSN=2038-4963
 
|ISSN=2038-4963
|Download=Clef2010Labs LOD Expertsearch.pdf,  
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|Download=Clef2010Labs LOD Expertsearch.pdf,
 
|Link=http://www.clef2010.org/index.php?page=pages/proceedings.php
 
|Link=http://www.clef2010.org/index.php?page=pages/proceedings.php
 
|Projekt=IGreen
 
|Projekt=IGreen

Version vom 17. September 2010, 14:48 Uhr


Multilingual Expert Search using Linked Open Data as Interlingual Representation


Multilingual Expert Search using Linked Open Data as Interlingual Representation



Published: 2010 September

Buchtitel: Working Notes of the CLEF 2010 Lab Sessions
Verlag: CLEF 2010

Referierte Veröffentlichung

BibTeX

Kurzfassung
Most Information Retrieval models take documents as Bag-of-Words and are thereby bound to the language of the documents. In this paper, we present an approach using Linked Open Data resources, i.e. URIs, as interlingual document representations. Documents and queries are summarized by the resources they contain. We show the applicability of our approach for multilingual retrieval with a case study on expert search.

ISBN: 978-88-904810-0-0
ISSN: 2038-4963
Download: Media:Clef2010Labs LOD Expertsearch.pdf
Weitere Informationen unter: Link

Projekt

IGreen



Forschungsgruppe

Wissensmanagement


Forschungsgebiet

Semantische Technologien, Vernetzte Daten, Information Retrieval