TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publication References
  4. BOEMIE : reasoning-based information extraction
 
Options

BOEMIE : reasoning-based information extraction

Publikationstyp
Conference Paper
Date Issued
2013
Sprache
English
Author(s)
Petasis, Georgios  
Möller, Ralf  
Karkaletsis, Vangelis  
Institut
Softwaresysteme E-16  
TORE-URI
http://hdl.handle.net/11420/7174
First published in
CEUR workshop proceedings  
Number in series
1044
Start Page
60
End Page
75
Citation
Natural language processing and automated reasoning 2013 : NLPAR 2013 ; proceedings of the 1st Workshop on Natural Language Processing and Automated Reasoning co-located with 12th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2013), A Corunna, Spain, September 15th, 2013 / ed. by Chitta Baral ... - Aachen : RWTH, 2013. - (CEUR Workshop Proceedings ; 1044). - Seite 60-75
Contribution to Conference
1st Workshop on Natural Language Processing and Automated Reasoning, NLPAR 2013  
Scopus ID
2-s2.0-84924403309
Publisher
RWTH Aachen
This paper presents a novel approach for exploiting an ontology in an ontology-based information extraction system, which substitutes part of the extraction process with reasoning, guided by a set of automatically acquired rules.
DDC Class
004: Informatik
TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback