April 5, 2024, 4:42 a.m. | Haonan Zhang, Dongxia Wang, Zhu Sun, Yanhui Li, Youcheng Sun, Huizhi Liang, Wenhai Wang

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.03164v1 Announce Type: cross
Abstract: Recommender systems (RSs) are designed to provide personalized recommendations to users. Recently, knowledge graphs (KGs) have been widely introduced in RSs to improve recommendation accuracy. In this study, however, we demonstrate that RSs do not necessarily perform worse even if the KG is downgraded to the user-item interaction graph only (or removed). We propose an evaluation framework KG4RecEval to systematically evaluate how much a KG contributes to the recommendation accuracy of a KG-based RS, using …

abstract accuracy arxiv cs.ai cs.ir cs.lg graph graphs however knowledge knowledge graph knowledge graphs matter personalized personalized recommendations recommendation recommendations recommender systems rss study systems type

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