Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference

arXiv:2404.19620v1 Announce Type: new
Abstract: Selection bias in recommender system arises from the recommendation process of system filtering and the interactive process of user selection. Many previous studies have focused on addressing selection bias to achieve unbiased learning of the prediction model, but ignore the fact that potential outcomes for a given user-item pair may vary with the treatments assigned to other user-item pairs, named neighborhood effect. To fill the gap, this paper formally formulates the neighborhood effect as an …

abstract arxiv bias cs.ir cs.lg filtering interactive interference modeling prediction process recommendation stat.ml studies type unbiased