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TindArt, an Experiment on User Profiling for Museum Applications

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Digital Libraries: The Era of Big Data and Data Science (IRCDL 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1177))

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Abstract

In this paper an Android application called TindArt is presented. It has been developed to investigate a way to profile the user in cultural contexts, through the application of Recommender Systems for museum visits in the future. The purpose of the research also includes the study of the User Experience with TindArt to understand how it could be used in a real museum context. Two pilot studies are also presented.

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Notes

  1. 1.

    ISTAT, I musei, le aree archeologiche e i monumenti in Italia. Anno 2017, https://www.istat.it/it/files//2019/01/Report-Musei_2017_con_loghi.pdf.

  2. 2.

    Global Attractions Attendance Report, Themed Entertainment Association (TEA) and the Economics practice at AECOM, 2018, https://www.aecom.com/content/wp-content/uploads/2019/05/Theme-Index-2018-5-1.pdf.

  3. 3.

    European Report CULTURAL ACCESS AND PARTICIPATION, 2013: http://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_399_en.pdf.

  4. 4.

    https://www.metmuseum.org/toah/.

  5. 5.

    https://www.metmuseum.org/art/collection/.

  6. 6.

    www.wikiart.com.

  7. 7.

    https://play.google.com/store/apps/details?id=tindar_evo.meeple.tindart.

  8. 8.

    https://play.google.com/store/apps/details?id=com.tinder.

  9. 9.

    The user account management is relegated to Google Firebase, https://firebase.google.com/.

  10. 10.

    https://developers.google.com/actions/deploy/release-environments.

References

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Author information

Authors and Affiliations

  1. Department of Cultural Heritage, University of Padua, Piazza Capitaniato, 7, 35139, Padua, Italy

    Daniel Zilio, Nicola Orio & Camilla Toniolo

Authors
  1. Daniel Zilio
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  2. Nicola Orio
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  3. Camilla Toniolo
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Corresponding author

Correspondence to Nicola Orio .

Editor information

Editors and Affiliations

  1. University of Bari, Bari, Italy

    Michelangelo Ceci

  2. University of Bari, Bari, Italy

    Stefano Ferilli

  3. Sapienza University of Rome, Rome, Italy

    Antonella Poggi

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Zilio, D., Orio, N., Toniolo, C. (2020). TindArt, an Experiment on User Profiling for Museum Applications. In: Ceci, M., Ferilli, S., Poggi, A. (eds) Digital Libraries: The Era of Big Data and Data Science. IRCDL 2020. Communications in Computer and Information Science, vol 1177. Springer, Cham. https://doi.org/10.1007/978-3-030-39905-4_13

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  • DOI: https://doi.org/10.1007/978-3-030-39905-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39904-7

  • Online ISBN: 978-3-030-39905-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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