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An Approach to Conversational Recommendation of Restaurants

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HCI International 2019 - Posters (HCII 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1034))

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Abstract

In this paper, we propose an approach based on the integration of a chatbot module, a location-based service, and a recommendation algorithm. This approach has been deployed for restaurant recommendation, tested on a sample of 50 real users, and compared with some state-of-the-art algorithms. The preliminary experimental results showed the benefits of the proposed approach in terms of performance. An ANOVA test enabled us to verify the statistical significance of the obtained findings.

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Notes

  1. 1.

    https://dialogflow.com/.

  2. 2.

    https://core.telegram.org/.

  3. 3.

    https://www.mongodb.com/.

  4. 4.

    https://developers.facebook.com/docs/graph-api.

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Author information

Authors and Affiliations

  1. Department of Engineering, Roma Tre University, Via della Vasca Navale 79, 00146, Rome, Italy

    Nicola Sardella, Claudio Biancalana, Alessandro Micarelli & Giuseppe Sansonetti

Authors
  1. Nicola Sardella
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  2. Claudio Biancalana
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  3. Alessandro Micarelli
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  4. Giuseppe Sansonetti
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Corresponding author

Correspondence to Giuseppe Sansonetti .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

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Sardella, N., Biancalana, C., Micarelli, A., Sansonetti, G. (2019). An Approach to Conversational Recommendation of Restaurants. In: Stephanidis, C. (eds) HCI International 2019 - Posters. HCII 2019. Communications in Computer and Information Science, vol 1034. Springer, Cham. https://doi.org/10.1007/978-3-030-23525-3_16

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  • DOI: https://doi.org/10.1007/978-3-030-23525-3_16

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  • Online ISBN: 978-3-030-23525-3

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