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Ontology-Based Information Extraction and Reasoning for Business Intelligence Applications

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KI 2008: Advances in Artificial Intelligence (KI 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5243))

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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.

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References

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Authors and Affiliations

  1. DFKI GmbH, Language Technology Lab, Stuhlsatzenhausweg, 3, 66123, Saarbrücken, Germany

    Thierry Declerck, Christian Federmann, Bernd Kiefer & Hans-Ulrich Krieger

Authors
  1. Thierry Declerck
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  2. Christian Federmann
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  3. Bernd Kiefer
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  4. Hans-Ulrich Krieger
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Editor information

Andreas R. Dengel Karsten Berns Thomas M. Breuel Frank Bomarius Thomas R. Roth-Berghofer

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© 2008 Springer-Verlag Berlin Heidelberg

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Declerck, T., Federmann, C., Kiefer, B., Krieger, HU. (2008). Ontology-Based Information Extraction and Reasoning for Business Intelligence Applications. In: Dengel, A.R., Berns, K., Breuel, T.M., Bomarius, F., Roth-Berghofer, T.R. (eds) KI 2008: Advances in Artificial Intelligence. KI 2008. Lecture Notes in Computer Science(), vol 5243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85845-4_48

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  • DOI: https://doi.org/10.1007/978-3-540-85845-4_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85844-7

  • Online ISBN: 978-3-540-85845-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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