no code implementations • COLING (TextGraphs) 2020 • Zhenqi Zhao, Yuchen Guo, Dingxian Wang, Yufan Huang, Xiangnan He, Bin Gu
Entity Resolution (ER) identifies records that refer to the same real-world entity.
no code implementations • 24 May 2024 • Yuyue Zhao, Jiancan Wu, Xiang Wang, Wei Tang, Dingxian Wang, Maarten de Rijke
Through the integration of LLMs, ToolRec enables conventional recommender systems to become external tools with a natural language interface.
no code implementations • 25 Oct 2023 • Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang
Therefore, the data sparsity issue of reward signals and state transitions is very severe, while it has long been overlooked by existing RL recommenders. Worse still, RL methods learn through the trial-and-error mode, but negative feedback cannot be obtained in implicit feedback recommendation tasks, which aggravates the overestimation problem of offline RL recommender.
no code implementations • 9 Aug 2023 • Kaize Shi, Xueyao Sun, Dingxian Wang, Yinlin Fu, Guandong Xu, Qing Li
E-commerce authoring involves creating attractive, abundant, and targeted promotional content to drive product sales.
1 code implementation • 26 Apr 2023 • Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang
However, such a manner inevitably learns unstable feature interactions, i. e., the ones that exhibit strong correlations in historical data but generalize poorly for future serving.
no code implementations • 16 Mar 2023 • Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying
Recently, there has been an increasing adoption of differential privacy guided algorithms for privacy-preserving machine learning tasks.
no code implementations • 25 Jan 2023 • Yunqi Li, Dingxian Wang, Hanxiong Chen, Yongfeng Zhang
The proposed method is able to transfer the knowledge of a fair model learned from the source users to the target users with the hope of improving the recommendation performance and keeping the fairness property on the target users.
1 code implementation • 20 Dec 2022 • Yinwei Wei, Xiang Wang, Liqiang Nie, Shaoyu Li, Dingxian Wang, Tat-Seng Chua
Knowledge Graph (KG), as a side-information, tends to be utilized to supplement the collaborative filtering (CF) based recommendation model.
no code implementations • 16 May 2022 • Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He
Towards this goal, we propose a Hidden Confounder Removal (HCR) framework that leverages front-door adjustment to decompose the causal effect into two partial effects, according to the mediators between item features and user feedback.
2 code implementations • 14 Feb 2021 • Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua
In this study, we explore intents behind a user-item interaction by using auxiliary item knowledge, and propose a new model, Knowledge Graph-based Intent Network (KGIN).
2 code implementations • 12 Nov 2018 • Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua
Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user's interest.
3 code implementations • 15 Aug 2017 • Xiangnan He, Ming Gao, Min-Yen Kan, Dingxian Wang
In this paper, we study the problem of ranking vertices of a bipartite graph, based on the graph's link structure as well as prior information about vertices (which we term a query vector).