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Statistical Profiles of Words for Ontology Enrichment

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Soft Methods in Probability, Statistics and Data Analysis

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 16))

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Abstract

The following paper focuses on an enrichment method for ontologies. We define similarities of possible new concepts and base the similarity and dissimilarity of concepts on the usage statistics in large corpora. The method is soft in the sense, that we define a semantically motivated heuristics for the influence of different linguistic properties influencing the similarity definition.

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References

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Author information

Authors and Affiliations

  1. Multimedia Communications Lab, Darmstadt University of Technology, Merckstrasse 25, 64283, Darmstadt, Germany

    Andreas Faatz, Cornelia Seeberg & Ralf Steinmetz

Authors
  1. Andreas Faatz
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  2. Cornelia Seeberg
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  3. Ralf Steinmetz
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Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Przemysław Grzegorzewski  & Olgierd Hryniewicz  & 

  2. Facultad de Ciencias, Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, C/Calvo Sotelo, s/n, 33007, Oviedo, Spain

    María Ángeles Gil

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© 2002 Springer-Verlag Berlin Heidelberg

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Faatz, A., Seeberg, C., Steinmetz, R. (2002). Statistical Profiles of Words for Ontology Enrichment. In: Grzegorzewski, P., Hryniewicz, O., Gil, M.Á. (eds) Soft Methods in Probability, Statistics and Data Analysis. Advances in Intelligent and Soft Computing, vol 16. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1773-7_30

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  • DOI: https://doi.org/10.1007/978-3-7908-1773-7_30

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1526-9

  • Online ISBN: 978-3-7908-1773-7

  • eBook Packages: Springer Book Archive

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