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Extended Semantic Web Conference

ESWC 2012: The Semantic Web: Research and Applications pp 4Cite as

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Large Scale Learning at Twitter

Large Scale Learning at Twitter

  • Aleksander Kołcz21 
  • Conference paper
  • 2783 Accesses

  • 1 Citations

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7295)

Abstract

Twitter represents a large complex network of users with diverse and continuously evolving interests. Discussions and interactions range from very small to very large groups of people and most of them occur in the public. Interests are both long and short term and are expressed by the content generated by the users as well as via the Twitter follow graph, i.e. who is following whose content.

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Authors and Affiliations

  1. Twitter, USA

    Aleksander Kołcz

Authors
  1. Aleksander Kołcz
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Editor information

Editors and Affiliations

  1. Institute AIFB, Karlsruhe Institute of Technology, Englerstrasse 11, 76131, Karlsruhe, Germany

    Elena Simperl

  2. CITEC, University of Bielefeld, Morgenbreede 39, 33615, Bielefeld, Germany

    Philipp Cimiano

  3. Siemens AG Österreich, Siemensstrasse 90, 1210, Vienna, Austria

    Axel Polleres

  4. Technical University of Madrid, C/ Severo Ochoa, 13, 28660, Boadilla del Monte, Madrid, Spain

    Oscar Corcho

  5. STLab, ISTC-CNR, Via Nomentana 56, 00161, Rome, Italy

    Valentina Presutti

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kołcz, A. (2012). Large Scale Learning at Twitter. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds) The Semantic Web: Research and Applications. ESWC 2012. Lecture Notes in Computer Science, vol 7295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30284-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-30284-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30283-1

  • Online ISBN: 978-3-642-30284-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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