Web: http://arxiv.org/abs/2201.05861

Jan. 27, 2022, 2:11 a.m. | Chengqiang Lu, Mingyang Yin, Shuheng Shen, Luo Ji, Qi Liu, Hongxia Yang

cs.LG updates on arXiv.org arxiv.org

Recommendation system has been a widely studied task both in academia and
industry. Previous works mainly focus on homogeneous recommendation and little
progress has been made for heterogeneous recommender systems. However,
heterogeneous recommendations, e.g., recommending different types of items
including products, videos, celebrity shopping notes, among many others, are
dominant nowadays. State-of-the-art methods are incapable of leveraging
attributes from different types of items and thus suffer from data sparsity
problems. And it is indeed quite challenging to represent items with …

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