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International Conference of the Italian Association for Artificial Intelligence

AI*IA 2018: AI*IA 2018 – Advances in Artificial Intelligence pp 528–538Cite as

Improving the User Experience with a Conversational Recommender System

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11298)

Abstract

Chatbots are becoming more and more popular for several applications like customer care, health care, medical diagnoses. Generally, they have an interaction with users based on natural language, buttons, or both. In this paper we study the user interaction with a content-based recommender system implemented as a Telegram chatbot. More specifically, we investigate on one hand what are the best strategies for reducing the cost of interaction for the users and, on the other hand how to improve their experience. Our chatbot is able to provide personalized recommendations in the movie domain and implements critiquing strategies for improving the recommendation accuracy as well. In a preliminary experimental evaluation, carried out through a user study, interesting results emerged.

Keywords

  • Conversational recommender system
  • Chatbot
  • User experience

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Fig. 1.
Fig. 2.
Fig. 3.

Notes

  1. 1.

    The chatbot can be tested by searching for @MovieRecSysBot in Telegram list of contacts.

  2. 2.

    http://wiki.dbpedia.org/.

  3. 3.

    The diversity is computed by the Jaccard index on the movie properties between the items in the user profile and the items not rated yet.

  4. 4.

    @MovieRecBot.

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Acknowledgment

This work has been funded by the projects UNIFIED WEALTH MANAGEMENT PLATFORM - OBJECTWAY SpA - Via Giovanni Da Procida nr. 24, 20149 MILANO - c.f., P. IVA 07114250967, and PON01 00850 ASK-Health (Advanced system for the interpretations and sharing of knowledge in health care).

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bari Aldo Moro, Via E. Orabona, 4, Bari, Italy

    Fedelucio Narducci, Marco de Gemmis, Pasquale Lops & Giovanni Semeraro

Authors
  1. Fedelucio Narducci
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  2. Marco de Gemmis
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  3. Pasquale Lops
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  4. Giovanni Semeraro
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Corresponding author

Correspondence to Fedelucio Narducci .

Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Povo (TN), Italy

    Chiara Ghidini

  2. Fondazione Bruno Kessler, Povo (TN), Italy

    Bernardo Magnini

  3. University of Trento, Povo (TN), Italy

    Andrea Passerini

  4. Fondazione Bruno Kessler, Povo (TN), Italy

    Paolo Traverso

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Narducci, F., de Gemmis, M., Lops, P., Semeraro, G. (2018). Improving the User Experience with a Conversational Recommender System. In: Ghidini, C., Magnini, B., Passerini, A., Traverso, P. (eds) AI*IA 2018 – Advances in Artificial Intelligence. AI*IA 2018. Lecture Notes in Computer Science(), vol 11298. Springer, Cham. https://doi.org/10.1007/978-3-030-03840-3_39

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  • DOI: https://doi.org/10.1007/978-3-030-03840-3_39

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