A Novel Time-Aware Food Recommender-System Based on Deep Learning and Graph Clustering
Food recommender-systems are considered an effective tool to help users adjust their eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food recommender-system to overcome the shortcomings of previous systems, such as ignoring food ingredients, time factor, cold star...
Saved in:
| Main Authors: | Mehrdad Rostami, Mourad Oussalah, Vahid Farrahi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9775081/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Attribute-Aware Graph Aggregation for Sequential Recommendation
by: Yiming Qu, et al.
Published: (2025-04-01) -
The Graph Attention Recommendation Method for Enhancing User Features Based on Knowledge Graphs
by: Hui Wang, et al.
Published: (2025-01-01) -
Light Graph Convolutional Recommendation Algorithm Based on Hybrid Spreading
by: Yaowei Duan, et al.
Published: (2025-02-01) -
Tourist attraction recommendation method combining graph attention network and clustering algorithm
by: Jiahua Xiang, et al.
Published: (2025-07-01) -
Interdependent-path Recurrent Embedding for Knowledge Graph-aware Recommendation
by: Xiao Sha, et al.
Published: (2025-06-01)