Improving the User Experience with a Conversational Recommender System

  • Fedelucio Narducci
  • Marco de Gemmis
  • Pasquale Lops
  • Giovanni Semeraro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)


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.


Conversational recommender system Chatbot User experience 



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).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Fedelucio Narducci
    • 1
  • Marco de Gemmis
    • 1
  • Pasquale Lops
    • 1
  • Giovanni Semeraro
    • 1
  1. 1.Department of Computer ScienceUniversity of Bari Aldo MoroBariItaly

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