An explainable content-based approach for recommender systems: a case study in journal recommendation for paper submission
Luis M. de Campos,
Juan M. Fernández-Luna,
Juan F. Huete
Abstract:Explainable artificial intelligence is becoming increasingly important in new artificial intelligence developments since it enables users to understand and consequently trust system output. In the field of recommender systems, explanation is necessary not only for such understanding and trust but also because if users understand why the system is making certain suggestions, they are more likely to consume the recommended product. This paper proposes a novel approach for explaining content-based recommender sys… Show more
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