When Multi-Level Meets Multi-Interest: A Multi-Grained Neural Model for Sequential Recommendation

1 code implementation • 3 May 2022 • Yu Tian, Jianxin Chang, Yannan Niu, Yang song, Chenliang Li

Specifically, multi-interest methods such as ComiRec and MIMN, focus on extracting different interests for a user by performing historical item clustering, while graph convolution methods including TGSRec and SURGE elect to refine user preferences based on multi-level correlations between historical items.

Sequential Recommendation