Güell, MarcSalamó Llorente, MariaContreras, DavidBoratto, Ludovico2023-03-022023-03-022020-121389-0417https://hdl.handle.net/2445/194426Recommender systems are cognitive computing systems designed to support humans in their decision-making processes through convincing, timely product suggestions. In the field of recommender systems, critique-based recommenders have been widely applied as an effective approach for guiding users through a product space in pursuit of suitable products. To date, no critique-based approach has included an assistant that support users in their search in a pleasant way. In this paper, we describe how we integrate an assistant within a critique-based recommender. We consider the proposed assistant to be cognitive because its reasoning process when recommending products is based on a cognitively-inspired clustering algorithm. The proposal is evaluated by users and compared with a non-assistant approach. The results of this research demonstrate that the integration of a cognitive assistant within the recommender improves the user experience and increases the performance of the recommendation process, i.e., users need fewer cycles to achieve the desired product or service.14 p.application/pdfengcc-by-nc-nd (c) Elsevier B.V., 2020https://creativecommons.org/licenses/by-nc-nd/4.0/Sistemes d'ajuda a la decisióIntel·ligència artificialTractament del llenguatge natural (Informàtica)Decision support systemsArtificial intelligenceNatural language processing (Computer science)info:eu-repo/semantics/article7093742023-03-02info:eu-repo/semantics/openAccess