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Describing Locations Using Tags and Images: Explorative Pattern Mining in Social Media

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Modeling and Mining Ubiquitous Social Media (MUSE 2011, MSM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7472))

Abstract

This paper presents an approach for explorative pattern mining in social media based on tagging information and collaborative geo-reference annotations. We utilize pattern mining techniques for obtaining sets of tags that are specific for the specified point, landmark, or region of interest. Next, we show how these candidate patterns can be presented and visualized for interactive exploration using a combination of general pattern mining visualizations and views specialized on geo-referenced tagging data. We present a case study using publicly available data from the Flickr photo sharing platform.

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Author information

Authors and Affiliations

  1. Artificial Intelligence and Applied Computer Science, University of Würzburg, 97074, Würzburg, Germany

    Florian Lemmerich

  2. Knowledge and Data Engineering Group, University of Kassel, Germany

    Martin Atzmueller

Authors
  1. Florian Lemmerich
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  2. Martin Atzmueller
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Editor information

Editors and Affiliations

  1. Knowledge and Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121, Kassel, Germany

    Martin Atzmueller

  2. Mobile Social Networking Group, Nokia Research Center, 100176, Beijing, China

    Alvin Chin

  3. Faculty of Computer Science, Graz University of Technology, Inffeldgasse 21a, 8010, Graz, Austria

    Denis Helic

  4. Data Mining and Information Retrieval Group, University of Würzburg, Am Hubland, 97074, Würzburg, Germany

    Andreas Hotho

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© 2012 Springer-Verlag Berlin Heidelberg

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Lemmerich, F., Atzmueller, M. (2012). Describing Locations Using Tags and Images: Explorative Pattern Mining in Social Media. In: Atzmueller, M., Chin, A., Helic, D., Hotho, A. (eds) Modeling and Mining Ubiquitous Social Media. MUSE MSM 2011 2011. Lecture Notes in Computer Science(), vol 7472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33684-3_5

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  • DOI: https://doi.org/10.1007/978-3-642-33684-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33683-6

  • Online ISBN: 978-3-642-33684-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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