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Adapting News and Advertisements to Groups

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Book cover Pervasive Advertising

Part of the book series: Human-Computer Interaction Series ((HCIS))

Abstract

This chapter deals with adaptation of background information and ­advertisements, displayed in an environment, to the interests of the group of people present. According to research on computational advertising, it is important to develop methods for finding the “best match” between user interests in a given context and available advertisements. Accordingly, after providing an overview of the most popular group recommender approaches, this chapter looks at new issues that arise when considering group modeling in pervasive advertising conveyed through digital displays. The chapter first discusses general issues concerning group recommender systems, with particular emphasis on the acquisition of user preferences and interests. A system called GAIN (Group Adaptive Information and News) is then presented. This was developed with the aim of tailoring the display of background information and advertisements to groups of people.

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Notes

  1. 1.

    A.S.D. BodyEnergy, Mola di Bari, Italy.

  2. 2.

    We wanted to express the confidence of each topic as a percentage. For this reason, we set P PROBABLE  =  f(PSURE), f being a function that relates these two values to one another.

  3. 3.

    This is valid if PSURE  +  PPROBABLE  =  1, otherwise, it is necessary to divide the value of Cj by the value of PSURE  +  PPROBABLE in order to obtain a result between 0 and 1.

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Acknowledgements

The author is grateful to Dr. Brian Bloch for his comprehensive editing of the manuscript.

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Authors and Affiliations

  1. University of Bari, Bari, Italy

    Berardina De Carolis

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  1. Berardina De Carolis
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Correspondence to Berardina De Carolis .

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Editors and Affiliations

  1. , Laboratories, Deutsche Telekom AG, Ernst-Reuter-Platz 7,, Berlin, 10587, Germany

    Jörg Müller

  2. University of Stuttgart, Pfaffenwaldring, Stuttgart, 70569, Germany

    Florian Alt

  3. Anhalt University of Applied Science, Strenzfelder Allee 28,, Bernburg, 06406, Germany

    Daniel Michelis

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De Carolis, B. (2011). Adapting News and Advertisements to Groups. In: Müller, J., Alt, F., Michelis, D. (eds) Pervasive Advertising. Human-Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-0-85729-352-7_11

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  • DOI: https://doi.org/10.1007/978-0-85729-352-7_11

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  • Print ISBN: 978-0-85729-351-0

  • Online ISBN: 978-0-85729-352-7

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