1 code implementation • 29 Mar 2022 • Zhifang Fan, Dan Ou, Yulong Gu, Bairan Fu, Xiang Li, Wentian Bao, Xin-yu Dai, Xiaoyi Zeng, Tao Zhuang, Qingwen Liu
In this paper, we propose a new perspective for context-aware users' behavior modeling by including the whole page-wisely exposed products and the corresponding feedback as contextualized page-wise feedback sequence.
no code implementations • 16 Dec 2021 • Rongzhi Zhang, Yulong Gu, Xiaoyu Shen, Hui Su
We introduce time interval embedding to represent the time pattern between the item that needs to be predicted and historical click, and use it to replace the position embedding in the original transformer (called temporal transformer).
1 code implementation • 4 Jul 2020 • Lixin Zou, Long Xia, Yulong Gu, Xiangyu Zhao, Weidong Liu, Jimmy Xiangji Huang, Dawei Yin
Therefore, the proposed exploration policy, to balance between learning the user profile and making accurate recommendations, can be directly optimized by maximizing users' long-term satisfaction with reinforcement learning.
1 code implementation • 29 Jun 2020 • Yulong Gu, Yu Guan, Paolo Missier
Many systems have been developed in recent years to mine logical rules from large-scale Knowledge Graphs (KGs), on the grounds that representing regularities as rules enables both the interpretable inference of new facts, and the explanation of known facts.
1 code implementation • 13 Mar 2020 • Yulong Gu, Yu Guan, Paolo Missier
Instantiated rules contain constants extracted from KGs.