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Improving Billboard Advertising Revenue Using Transactional Modeling and Pattern Mining

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Book cover Database and Expert Systems Applications (DEXA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12923))

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Abstract

Billboard advertisement is among the dominant modes of outdoor advertisements. The billboard operator has an opportunity to improve its revenue by satisfying the advertising demands of an increased number of clients by means of exploiting the user trajectory data. Hence, we introduce the problem of billboard advertisement allocation for improving the billboard operator revenue, and propose an efficient user trajectory-based transactional framework using coverage pattern mining. Our experiments validate the effectiveness of our framework.

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Notes

  1. 1.

    https://www.openstreetmap.org.

  2. 2.

    https://graphhopper.com/api/1/docs/map-matching/.

  3. 3.

    https://nominatim.openstreetmap.org/.

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Author information

Authors and Affiliations

  1. IIIT Hyderabad, Hyderabad, India

    P. Revanth Rathan & P. Krishna Reddy

  2. Ashoka University, Sonipat, India

    Anirban Mondal

Authors
  1. P. Revanth Rathan
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  2. P. Krishna Reddy
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  3. Anirban Mondal
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Corresponding author

Correspondence to P. Revanth Rathan .

Editor information

Editors and Affiliations

  1. University of Vienna, Vienna, Austria

    Christine Strauss

  2. Johannes Kepler University of Linz, Linz, Oberösterreich, Austria

    Gabriele Kotsis

  3. Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  4. Johannes Kepler University of Linz, Linz, Austria

    Ismail Khalil

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Rathan, P.R., Reddy, P.K., Mondal, A. (2021). Improving Billboard Advertising Revenue Using Transactional Modeling and Pattern Mining. In: Strauss, C., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2021. Lecture Notes in Computer Science(), vol 12923. Springer, Cham. https://doi.org/10.1007/978-3-030-86472-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-86472-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86471-2

  • Online ISBN: 978-3-030-86472-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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