Towards trustworthy recommenders: building explainable and unbiased recommendation systems
The explosively increasing online content, such as exposure on e-commerce platforms (e.g., Amazon and Taobao), makes it very difficult for users to choose suitable items or information from the vast volume of options available. To address this problem, recommendation systems have been widely used to...
Saved in:
Main Author: | Hu, Yidan |
---|---|
Other Authors: | Miao Chun Yan |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175790 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Aspect-guided syntax graph learning for explainable recommendation
by: Hu, Yidan, et al.
Published: (2023) -
Personalized fashion recommendation with visual explanations based on multimodal attention network: Towards visually explainable recommendation
by: CHEN, Xu, et al.
Published: (2019) -
Hypergraphs with attention on reviews for explainable recommendation
by: JENDAL, Theis E., et al.
Published: (2024) -
Explainable reasoning over knowledge graphs for recommendation
by: WANG, Xiang, et al.
Published: (2019) -
LightGCNxGPT: integrating LightGCN with GPT for enhanced personalised recommendations and explainability in recommender systems
by: Tiyyagura, Rochana
Published: (2024)