no code implementations • 23 Feb 2024 • Zijun Long, Xuri Ge, Richard McCreadie, Joemon Jose
Text-to-image retrieval aims to find the relevant images based on a text query, which is important in various use-cases, such as digital libraries, e-commerce, and multimedia databases.
no code implementations • 27 Aug 2023 • Yu Wang, Xin Xin, Zaiqiao Meng, Joemon Jose, Fuli Feng
We employ the proposed DeCA on both the binary label scenario and the multiple label scenario.
1 code implementation • 9 May 2023 • Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose, Maarten de Rijke, Zhaochun Ren
Recommender systems that learn from implicit feedback often use large volumes of a single type of implicit user feedback, such as clicks, to enhance the prediction of sparse target behavior such as purchases.
no code implementations • 20 May 2021 • Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng
A noisy negative example which is uninteracted because of unawareness of the user could also denote potential positive user preference.
2 code implementations • 29 Sep 2020 • Fajie Yuan, Guoxiao Zhang, Alexandros Karatzoglou, Joemon Jose, Beibei Kong, Yudong Li
In this paper, we delve on research to continually learn user representations task by task, whereby new tasks are learned while using partial parameters from old ones.
2 code implementations • 29 Apr 2019 • Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, Joemon Jose
In this work, we propose Relational Collaborative Filtering (RCF), a general framework to exploit multiple relations between items in recommender system.