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Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform

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Innovations in Big Data Mining and Embedded Knowledge

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 159))

Abstract

Designing e-services for tourist today implies to deal with a large amount of data and metadata that developers should be able to exploit for generating user perceived values. By integrating a Recommender System on a Big Data platform, we constructed the horizontal infrastructure for managing these services in an application-neutral layer. In this chapter, we revise the design choices followed to implement this service layer, highlighting the data processing and architectural patterns we selected. More specifically, we first introduce the relevant notions related to Big Data technologies, we discussed the evolving trends in Tourism, and we introduce fundaments for designing Recommender Systems. This part provides us with a set of requirements to be fulfilled in order to integrate these different components. We then propose an architecture and a set of algorithms to support these requirements. This design process guided the implementation of an innovative e-service platform for tourist operators in Italy.

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Notes

  1. 1.

    This represents the distance between two activities, not the similarity, but we can still easily get, for each activity, the most similar ones by sorting according to the distance, ascending.

  2. 2.

    https://developers.facebook.com/docs/facebook-login.

  3. 3.

    https://www.scipy.org/.

  4. 4.

    https://www.mongodb.com.

  5. 5.

    https://spark.apache.org/.

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Acknowledgements

This work was partly supported by the “eTravel project” funded by the“Provincia di Trento”, and by the program “Piano sostegno alla ricerca 2015–17” funded by Università degli Studi di Milano.

Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Milano, via bramante 65, 26013, Crema, Italy

    Valerio Bellandi, Paolo Ceravolo & Ernesto Damiani

  2. Universitá Cattolica di Piacenza-Cremona, Via Emilia Parmense 84, 29122, Piacenza, Italy

    Eugenio Tacchini

Authors
  1. Valerio Bellandi
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  2. Paolo Ceravolo
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  3. Ernesto Damiani
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  4. Eugenio Tacchini
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Corresponding author

Correspondence to Valerio Bellandi .

Editor information

Editors and Affiliations

  1. Dipartimento di Psicologia and International Institute for Advanced Scientific Studies (IIASS), Università degli Studi della Campania “Luigi Vanvitelli”, Caserta, Italy

    Anna Esposito

  2. Sezione di Napoli, Osservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia, Napoli, Italy

    Antonietta M. Esposito

  3. University of Canberra, Canberra, ACT, Australia

    Lakhmi C. Jain

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Bellandi, V., Ceravolo, P., Damiani, E., Tacchini, E. (2019). Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform. In: Esposito, A., Esposito, A., Jain, L. (eds) Innovations in Big Data Mining and Embedded Knowledge. Intelligent Systems Reference Library, vol 159. Springer, Cham. https://doi.org/10.1007/978-3-030-15939-9_2

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