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The Synergies of Context and Data Aging in Recommendations

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Big Data Analytics and Knowledge Discovery (DaWaK 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14148))

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Abstract

In this paper, we investigate the synergies of data aging and contextual information in data mining techniques used to infer frequent, up-to-date, and contextual user behaviours that enable making recommendations on actions to take or avoid in order to fulfill a specific positive goal. We conduct experiments in two different domains: wearable devices and smart TVs.

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Author information

Authors and Affiliations

  1. University of Verona, Strada Le Grazie, 15, Verona, Italy

    Anna Dalla Vecchia, Niccolò Marastoni, Barbara Oliboni & Elisa Quintarelli

Authors
  1. Anna Dalla Vecchia
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  2. Niccolò Marastoni
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  3. Barbara Oliboni
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  4. Elisa Quintarelli
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Corresponding author

Correspondence to Elisa Quintarelli .

Editor information

Editors and Affiliations

  1. Poznań University of Technology, Poznan, Poland

    Robert Wrembel

  2. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Johann Gamper

  3. Johannes Kepler University Linz, Linz, Austria

    Gabriele Kotsis

  4. Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  5. Johannes Kepler University Linz, Linz, Austria

    Ismail Khalil

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Dalla Vecchia, A., Marastoni, N., Oliboni, B., Quintarelli, E. (2023). The Synergies of Context and Data Aging in Recommendations. In: Wrembel, R., Gamper, J., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2023. Lecture Notes in Computer Science, vol 14148. Springer, Cham. https://doi.org/10.1007/978-3-031-39831-5_7

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  • DOI: https://doi.org/10.1007/978-3-031-39831-5_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-39830-8

  • Online ISBN: 978-3-031-39831-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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