Conversational systems are increasing their popularity since they allow users to interact in a simple and natural way. Information Retrieval (IR) and Recommender Systems (RS) represents two categories of systems that strongly rely on the interaction with the user. For these reasons, recently many researches increased their effort towards the development Conversational Information Retrieval (CIR) and Conversational Recommender Systems (CRS). Such systems, in fact, allow to increase the ease of use from the user perspective and also to improve the quality of the results. The aim of this tutorial is to show the best and most frequently used approaches/paradigms to build CIR and CRS systems and to understand how these can be evaluated. During the tutorial the participants will be provided with the knowledge that is needed to understand, create and evaluate CIR and CRS.

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Conversational Information Retrieval and Recommender Systems

  • Guglielmo Faggioli,
  • Nicola Ferro,
  • Simone Merlo

摘要

Conversational systems are increasing their popularity since they allow users to interact in a simple and natural way. Information Retrieval (IR) and Recommender Systems (RS) represents two categories of systems that strongly rely on the interaction with the user. For these reasons, recently many researches increased their effort towards the development Conversational Information Retrieval (CIR) and Conversational Recommender Systems (CRS). Such systems, in fact, allow to increase the ease of use from the user perspective and also to improve the quality of the results. The aim of this tutorial is to show the best and most frequently used approaches/paradigms to build CIR and CRS systems and to understand how these can be evaluated. During the tutorial the participants will be provided with the knowledge that is needed to understand, create and evaluate CIR and CRS.