no code implementations • 23 May 2024 • Lei Zheng, Ning li, Yanhuan Huang, Ruiwen Xu, Weinan Zhang, Yong Yu
In this paper, we propose a novel framework of sequential recommendation called Look into the Future (LIFT), which builds and leverages the contexts of sequential recommendation.
no code implementations • 19 Mar 2024 • Yifan Liu, Kangning Zhang, Xiangyuan Ren, Yanhua Huang, Jiarui Jin, Yingjie Qin, Ruilong Su, Ruiwen Xu, Weinan Zhang
In AlignRec, the recommendation objective is decomposed into three alignments, namely alignment within contents, alignment between content and categorical ID, and alignment between users and items.
no code implementations • 12 Jul 2021 • Yanhua Huang, Weikun Wang, Lei Zhang, Ruiwen Xu
Content feed, a type of product that recommends a sequence of items for users to browse and engage with, has gained tremendous popularity among social media platforms.