DRSoRec: Dual-Rectification of Social Networks for Recommendation

Liangxun Yang; Tianzi Zang; Jiayi Sun; Juan Li; Yicong Li

AAAI 2026technical0 citations

DRSoRec: Dual-Rectification of Social Networks for Recommendation

Liangxun Yang, Tianzi Zang, Jiayi Sun, Juan Li, Yicong Li

Abstract

Leveraging social homophily to enhance user preference modeling, social recommendation has become a cornerstone of modern recommender systems. However, the raw social network contains inherent unreliability as it teems with noise---misclicks, bot-generated and transient ties---while many meaningful links remain unobserved. In this study, we propose DRSoRec, a dual-rectification model to rectify the raw social networks by simultaneously removing noisy signals and preserving useful information. Specifically, the invariant social rationale discovery module distills each user

BibTeX

@inproceedings{aaai2026_drsorecdualrecti,
  title = {DRSoRec: Dual-Rectification of Social Networks for Recommendation},
  author = {Liangxun Yang and Tianzi Zang and Jiayi Sun and Juan Li and Yicong Li},
  booktitle = {AAAI 2026},
  year = {2026}
}