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A Personalized and Context-Aware News Offer for Mobile Devices

  • Conference paper
Web Information Systems and Technologies (WEBIST 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 246))

Abstract

For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer.

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Notes

  1. 1.

    http://www.iminds.be/en/projects/2014/04/17/stream-store.

  2. 2.

    http://www.openlivinglabs.eu/livinglab/iminds-ilabo.

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Authors and Affiliations

  1. Department of Information Technology, iMinds, Ghent University, G. Crommenlaan 8/201, 9050, Ghent, Belgium

    Toon De Pessemier, Kris Vanhecke & Luc Martens

Authors
  1. Toon De Pessemier
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  2. Kris Vanhecke
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  3. Luc Martens
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Corresponding author

Correspondence to Toon De Pessemier .

Editor information

Editors and Affiliations

  1. University of Paris, Paris, France

    Valérie Monfort

  2. RWTH Aachen University, Aachen, Germany

    Karl-Heinz Krempels

  3. Department of Information Systems, University of Agder, Kristiansand, Vest-Agder Fylke, Norway

    Tim A. Majchrzak

  4. Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia

    Žiga Turk

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De Pessemier, T., Vanhecke, K., Martens, L. (2016). A Personalized and Context-Aware News Offer for Mobile Devices. In: Monfort, V., Krempels, KH., Majchrzak, T.A., Turk, Ž. (eds) Web Information Systems and Technologies. WEBIST 2015. Lecture Notes in Business Information Processing, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-319-30996-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-30996-5_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30995-8

  • Online ISBN: 978-3-319-30996-5

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