Users' Responsiveness to Persuasive Techniques in Recommender Systems.

ABSTRACT: Understanding user's behavior and their interactions with artificial-intelligent-based systems is as important as analyzing the performance of the algorithms used in these systems. For instance, in the Recommender Systems domain, the accuracy of the recommendation algorithm was the ultimate goal for most systems designers. However, researchers and practitioners have realized that providing accurate recommendations is insufficient to enhance users' acceptance. A recommender system needs to focus on other factors that enhance its interactions with the users. Recent researches suggest augmenting these systems with persuasive capabilities. Persuasive features lead to increasing users' acceptance of the recommendations, which, in turn, enhances users' experience with these systems. Nonet

SUBMITTER: Alslaity A 

PROVIDER: S-EPMC8297385 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature