Ontology-Based Information Extraction and Reasoning for Business Intelligence Applications

  • Authors:

  • Thierry Declerck;Christian Federmann;Bernd Kiefer;Hans-Ulrich Krieger

  • Affiliations:

  • DFKI GmbH, Language Technology Lab, Saarbrücken, Germany 66123;DFKI GmbH, Language Technology Lab, Saarbrücken, Germany 66123;DFKI GmbH, Language Technology Lab, Saarbrücken, Germany 66123;DFKI GmbH, Language Technology Lab, Saarbrücken, Germany 66123

  • Venue:
  • KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
  • Year:
  • 2008

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Abstract

In this demo we present the actual state of development of ontology-based information extraction in real world applications, as they are defined in the context of the MUSING European R&D project dealing with Business Intelligence applications. We present in some details the actual state of ontology development, including a time and domain ontologies, for guiding information extraction onto an ontology population task. We then show how the information is stored in the MUSING knowledge repository and how reasoning can act on this repository for generating new knowledge and also applications specific statistical models for supporting decision procedures.