Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2067/49391
Titolo: Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS)
Autori: Anelli, Vito Walter
Basile, Pierpaolo
De Melo, Gerard
Donini, Francesco Maria 
Ferrara, Antonio
Musto, Cataldo
Narducci, Fedelucio
Ragone, Azzurra
Zanker, Markus
Data pubblicazione: 2022
In the last few years, a renewed interest of the research community in conversational recommender systems (CRSs) has been emerging. This is likely due to the massive proliferation of Digital Assistants (DAs) such as Amazon Alexa, Siri, or Google Assistant that are revolutionizing the way users interact with machines. DAs allow users to execute a wide range of actions through an interaction mostly based on natural language utterances. However, although DAs are able to complete tasks such as sending texts, making phone calls, or playing songs, they still remain at an early stage in terms of their recommendation capabilities via a conversation. In addition, we have been witnessing the advent of increasingly precise and powerful recommendation algorithms and techniques able to effectively assess users' tastes and predict information that may be of interest to them. Most of these approaches rely on the collaborative paradigm (often exploiting machine learning techniques) and neglect the huge amount of knowledge, both structured and unstructured, describing the domain of interest of a recommendation engine. Although very effective in predicting relevant items, collaborative approaches miss some very interesting features that go beyond the accuracy of results and move in the direction of providing novel and diverse results as well as generating explanations for recommended items. Knowledge-aware side information becomes crucial when a conversational interaction is implemented, in particular for preference elicitation, explanation, and critiquing steps.
URI: http://hdl.handle.net/2067/49391
ISBN: 9781450392785
DOI: 10.1145/3523227.3547412
Diritti: Attribution-NonCommercial-NoDerivatives 4.0 International
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