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Matching Points of Interest from Different Social Networking Sites

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KI 2012: Advances in Artificial Intelligence (KI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7526))

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Abstract

Valuable user-generated information about locations (points of interest, POIs) is stored in various online social media platforms. Merging the data associated with one POI is hard because the platforms lack common identifiers. In addition, user-generated data is commonly faulty or contradictory. Here we present an approach matching POIs from Qype and Facebook Places to their counterparts in OpenStreetMap. The algorithm uses different similarity measures taking the geographic distance of POIs into account as well as the string similarity of selected metadata fields, showing good results.

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Author information

Authors and Affiliations

  1. DFKI GmbH, Alt-Moabit 91c, 10559, Berlin, Germany

    Tatjana Scheffler & Rafael Schirru

  2. University of Kaiserslautern, Gottlieb-Daimler-Strasse, 67663, Kaiserslautern, Germany

    Rafael Schirru

  3. Brandenburg University of Applied Sciences, Magdeburger Str. 50, 14770, Brandenburg an der Havel, Germany

    Paul Lehmann

Authors
  1. Tatjana Scheffler
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  2. Rafael Schirru
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  3. Paul Lehmann
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Editor information

Editors and Affiliations

  1. Institute of Artificial Intelligence, University of Ulm, 89069, Ulm, Germany

    Birte Glimm

  2. Saarland University and German Research Center for Artificial Intelligence (DFKI), Stuhlsatzenhausweg 3, 66123, Saarbrücken, Germany

    Antonio Krüger

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© 2012 Springer-Verlag Berlin Heidelberg

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Scheffler, T., Schirru, R., Lehmann, P. (2012). Matching Points of Interest from Different Social Networking Sites. In: Glimm, B., Krüger, A. (eds) KI 2012: Advances in Artificial Intelligence. KI 2012. Lecture Notes in Computer Science(), vol 7526. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33347-7_24

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  • DOI: https://doi.org/10.1007/978-3-642-33347-7_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33346-0

  • Online ISBN: 978-3-642-33347-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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