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Connectivity Inferences over the Web for the Analysis of Semantic Networks

  • Conference paper
Web and Wireless Geographical Information Systems (W2GIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3833))

Abstract

The World Wide Web constitutes a large information space and a promising support for the development of data inference, analysis and mining mechanisms. The research presented in this paper introduces a modelling approach that derives a social network and computes some of its emerging properties, from the semantics exhibited from a domain knowledge embedded in a series of Web pages. The framework is applied to the research communities related to a series of conferences in a given domain, and the university connections materialised by the researcher trajectories over time. The properties of the social network are analysed using graph-based measures, and a novel geographical dispersion coefficient.

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Author information

Authors and Affiliations

  1. Department of Geomatic Engineering, University College, London, UK

    Roderic Béra

  2. Naval Academy Research Institute, Lanvéoc-Poulmic, BP 600, 29240, Brest Naval, France

    Christophe Claramunt

Authors
  1. Roderic Béra
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  2. Christophe Claramunt
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Pusan National University, 609-735, Pusan, South Korea

    Ki-Joune Li

  2. EPFL, P.O. Box, Switzerland

    Christelle Vangenot

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© 2005 Springer-Verlag Berlin Heidelberg

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Béra, R., Claramunt, C. (2005). Connectivity Inferences over the Web for the Analysis of Semantic Networks. In: Li, KJ., Vangenot, C. (eds) Web and Wireless Geographical Information Systems. W2GIS 2005. Lecture Notes in Computer Science, vol 3833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599289_19

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  • DOI: https://doi.org/10.1007/11599289_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30848-5

  • Online ISBN: 978-3-540-32423-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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