Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. (arXiv:2208.01709v1 [cs.IR])

Implicit feedback is frequently used for developing personalized
recommendation services due to its ubiquity and accessibility in real-world
systems. In order to effectively utilize such information, most research adopts
the pairwise ranking method on constructed training triplets (user, positive
item, negative item) and aims to distinguish between positive items and
negative items for each user. However, most of these methods treat all the
training triplets equally, which ignores the subtle difference between
different positive or negative items. On the other …

arxiv feedback importance personalized recommendation