no code implementations • 6 Jan 2024 • Qian Li, Lixin Su, Jiashu Zhao, Long Xia, Hengyi Cai, Suqi Cheng, Hengzhu Tang, Junfeng Wang, Dawei Yin
Compared to conventional textual retrieval, the main obstacle for text-video retrieval is the semantic gap between the textual nature of queries and the visual richness of video content.
1 code implementation • 4 May 2023 • Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, Chao Huang
Recent studies show that graph neural networks (GNNs) are prevalent to model high-order relationships for collaborative filtering (CF).
no code implementations • 19 Oct 2022 • Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin
To address the above challenges, we propose a Bias Agnostic whole-page unbiased Learning to rank algorithm, named BAL, to automatically find the user behavior model with causal discovery and mitigate the biases induced by multiple SERP features with no specific design.
no code implementations • 14 Jul 2022 • Boming Zhao, Bangbang Yang, Zhenyang Li, Zuoyue Li, Guofeng Zhang, Jiashu Zhao, Dawei Yin, Zhaopeng Cui, Hujun Bao
Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications.
1 code implementation • 26 Apr 2022 • Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy Xiangji Huang
Additionally, our HCCF model effectively integrates the hypergraph structure encoding with self-supervised learning to reinforce the representation quality of recommender systems, based on the hypergraph-enhanced self-discrimination.
no code implementations • 31 Mar 2022 • Weiqi Shao, Xu Chen, Long Xia, Jiashu Zhao, Dawei Yin
To solve this problem, in this paper, we propose a novel sequential recommender model via decomposing and modeling user independent preferences.
1 code implementation • 17 Feb 2022 • Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, Dawei Yin
In addition, to capture the diverse multi-behavior patterns, we design a contrastive meta network to encode the customized behavior heterogeneity for different users.
no code implementations • 6 Dec 2021 • Weiqi Shao, Xu Chen, Jiashu Zhao, Long Xia, Dawei Yin
It is necessary to learn a dynamic group of representations according the item groups in a user historical behavior.
no code implementations • 6 Dec 2021 • Weiqi Shao, Xu Chen, Jiashu Zhao, Long Xia, Dawei Yin
We propose a sequential model with dynamic number of representations for recommendation systems (RDRSR).
1 code implementation • 8 Oct 2021 • Chao Huang, Jiahui Chen, Lianghao Xia, Yong Xu, Peng Dai, Yanqing Chen, Liefeng Bo, Jiashu Zhao, Jimmy Xiangji Huang
The learning process of intra- and inter-session transition dynamics are integrated, to preserve the underlying low- and high-level item relationships in a common latent space.