SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation

Abstract

Dealing with sparse, long-tailed datasets, and coldstart problems is always a challenge for recommender systems. These issues can partly be dealt with by making predictions not in isolation, but by leveraging information from related events; such information could include signals from social relationships or from the sequence of recent activities. Both… (More)
DOI: 10.24963/ijcai.2017/204

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