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The Effect of Context on Semantic Similarity Measurement

  • Conference paper
On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops (OTM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4806))

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Abstract

Similarity measurement is currently being established as a method to explore content on the Semantic Web. Semantically annotated content requires formal concept specifications. Such concepts are dynamic and their semantics can change depending on the current context. The influence of context on similarity measurement is beyond dispute and reflected in recent similarity theories. However, the systematics of this influence has not been investigated so far. Intuitively, the results of similarity measurements should change depending on the impact of the current context. Particularly, such change should converge to 0 with a decreasing impact of the respective contexts. To hold up to this assertion, a quantification of the impact of context on similarity measurements is required. In this paper, we use a combination of the SIM-DL theory, which measures similarity between concepts represented using description logic, and a context model distinguishing between internal and external context to quantify this impact. The behavior of similarity measurements within an ontology specifying geospatial feature types is observed under varying contexts. The results are discussed with respect to the corresponding impact values.

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Authors and Affiliations

  1. Institute for Geoinformatics, University of Münster, Germany

    Carsten Keßler & Krzysztof Janowicz

  2. Department of Geography, University of California at Santa Barbara, USA

    Martin Raubal

Authors
  1. Carsten Keßler
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  2. Martin Raubal
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  3. Krzysztof Janowicz
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Robert Meersman Zahir Tari Pilar Herrero

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Keßler, C., Raubal, M., Janowicz, K. (2007). The Effect of Context on Semantic Similarity Measurement. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops. OTM 2007. Lecture Notes in Computer Science, vol 4806. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76890-6_55

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  • DOI: https://doi.org/10.1007/978-3-540-76890-6_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76889-0

  • Online ISBN: 978-3-540-76890-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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