Personalized Preference Drift Aware Sequential Recommender System
The user preference patterns are highly dynamic and develop over time. To address the drift of user preference patterns, most of the prior works for sequential recommendation categorize the user preference patterns into different patterns, e.g., short-term and long-term preference. However, the numb...
Saved in:
| Main Authors: | Nakarin Sritrakool, Saranya Maneeroj |
|---|---|
| Format: | article |
| Language: | EN |
| Published: |
IEEE
2021
|
| Subjects: | |
| Online Access: | https://doaj.org/article/3512a8adfa7643689c715f8fcc12f5a4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Hybrid-Preference Neural Model for Basket-Sensitive Item Recommendation
by: Zhiqiang Pan, et al.
Published: (2020) -
NeuSub: A Neural Submodular Approach for Citation Recommendation
by: Binh Thanh Kieu, et al.
Published: (2021) -
Application of Intelligent Recommendation for Agricultural Information: A Systematic Literature Review
by: Caixia Song, et al.
Published: (2021) -
Using Artificial Neural Network for Predicting and Evaluating Situation Awareness of Operator
by: Shengyuan Yan, et al.
Published: (2021) -
Selective Untargeted Evasion Attack: An Adversarial Example That Will Not Be Classified as Certain Avoided Classes
by: Hyun Kwon, et al.
Published: (2019)