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A Framework for Analyzing News Images and Building Multimedia-Based Recommender

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Innovations for Community Services (I4CS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1041))

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Abstract

The number and accessibility of published news items have grown recently. Publishers have developed recommender systems supporting users in finding relevant news. Traditional news recommender systems focus on collaborative filtering and content-based strategies. Unlike texts, multimedia content has received little attention. However, images and other multimedia elements affect how users perceive the news. In this work, we present a system that aggregates text-based, image-based, and user interests-based features to foster recommender systems for news. The system monitors a live stream of news and interactions with them. It applies text analysis and automatic image labeling methods for enriching the news stream. A web application visualizes the collected data and statistics. We show that image features are valuable for developing news recommender systems. The created feature-rich dataset constitutes the basis for developing innovative news recommendation approaches.

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Notes

  1. 1.

    http://www.newsreelchallenge.org/.

  2. 2.

    http://www.acmmm.org/.

  3. 3.

    http://www.imageclef.org/.

  4. 4.

    http://www.multimediaeval.org/.

  5. 5.

    http://www.image-net.org/.

  6. 6.

    https://flask.pocoo.org/.

  7. 7.

    https://jinja.pocoo.org/.

  8. 8.

    https://startbootstrap.com/template-overviews/sb-admin/.

  9. 9.

    https://www.sqlalchemy.org/.

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Authors and Affiliations

  1. Agent Technologies in Business Applications and Telecommunication, Technische Universität Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany

    Andreas Lommatzsch, Benjamin Kille, Kevin Styp-Rekowski, Max Karl & Jan Pommering

Authors
  1. Andreas Lommatzsch
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  2. Benjamin Kille
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  3. Kevin Styp-Rekowski
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  4. Max Karl
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  5. Jan Pommering
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Corresponding author

Correspondence to Andreas Lommatzsch .

Editor information

Editors and Affiliations

  1. Faculty of Business, Ostfalia University of Applied Sciences, Wolfsburg, Niedersachsen, Germany

    Karl-Heinz Lüke

  2. Telekom Innovation Laboratories, Deutsche Telekom AG, Darmstadt, Hessen, Germany

    Gerald Eichler

  3. Ernst Abbe University of Applied Sciences Jena, Jena, Thüringen, Germany

    Christian Erfurth

  4. University of Hagen, Hagen, Nordrhein-Westfalen, Germany

    Günter Fahrnberger

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Lommatzsch, A., Kille, B., Styp-Rekowski, K., Karl, M., Pommering, J. (2019). A Framework for Analyzing News Images and Building Multimedia-Based Recommender. In: Lüke, KH., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2019. Communications in Computer and Information Science, vol 1041. Springer, Cham. https://doi.org/10.1007/978-3-030-22482-0_14

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  • DOI: https://doi.org/10.1007/978-3-030-22482-0_14

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  • Print ISBN: 978-3-030-22481-3

  • Online ISBN: 978-3-030-22482-0

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