Abstract
Recommender systems are frequently evaluated using performance indexes based on variants and extensions of precision-like measures. As these measures are biased toward popular items, a list of recommendations simply must include a few popular items to perform well. To address the popularity bias challenge, new approaches for novelty and diversity evaluation have been proposed. On the one hand, novelty-based approaches model the quality of being new as apposed to that which is already known. Novelty approaches are commonly based on item views or user rates. On the other hand, diversity approaches model the quality of an item that is composed of different content elements. Diversity measures are commonly rooted in content-based features that characterize the diversity of the content of an item in terms of the presence/absence of a number of predefined nuggets of information. As item contents are also biased to popular contents (e.g., drama in movies or pop in music), diversity-based measures are also popularity biased. To alleviate the effect of popularity bias on diversity measures, we used an evaluation approach based on the degree of novelty of the elements that make up each item. We named this approach content novelty, as it mixes content and diversity approaches in a single and coherent evaluation framework. Experimental results show that our proposal is feasible and useful. Our findings demonstrate that the proposed measures yield consistent and interpretable results, producing insights that reduce the impact of popularity bias in the evaluation of recommender systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.