no code implementations • 10 Oct 2023 • Tong Guo, Xuanping Li, Haitao Yang, Xiao Liang, Yong Yuan, Jingyou Hou, Bingqing Ke, Chao Zhang, Junlin He, Shunyu Zhang, Enyun Yu, WenWu
The overall historical behaviors are various but noisy while search behaviors are always sparse.
1 code implementation • 14 Oct 2022 • Yihong Tang, Junlin He, Zhan Zhao
To address these issues, we present Hierarchical Graph Attention Recurrent Network (HGARN) for human mobility prediction.
no code implementations • 16 Jul 2022 • Wei Wu, Junlin He, Yu Qiao, Guoheng Fu, Li Liu, Jin Yu
The in-memory approximate nearest neighbor search (ANNS) algorithms have achieved great success for fast high-recall query processing, but are extremely inefficient when handling hybrid queries with unstructured (i. e., feature vectors) and structured (i. e., related attributes) constraints.