Continual collaborative filtering through gradient alignment
A recommender system operates in a dynamic environment where new items emerge and new users join the system, resulting in ever-growing user-item interactions over time. Existing works either assume a model trained offline on a static dataset (requiring periodic re-training with ever larger datasets)...
Saved in:
Main Authors: | DO, Dinh Hieu, LAUW, Hady Wirawan |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8269 https://ink.library.smu.edu.sg/context/sis_research/article/9272/viewcontent/ContinualCollabFilter_GA_recsys23_av.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Collaborative topic regression with denoising AutoEncoder for content and community co-representation
by: NGUYEN, Trong T., et al.
Published: (2017) -
The wisdom of the few: A collaborative filtering approach based on expert opinions from the web
by: AMATRIAIN, Xavier, et al.
Published: (2009) -
Online multi-task collaborative filtering for on-the-fly recommender systems
by: WANG, Jialei, et al.
Published: (2013) -
Cornac-AB : An open-source recommendation framework with native A/B testing integration
by: ONG, Rong Sheng, et al.
Published: (2024) -
A theoretical analysis of query selection for collaborative filtering
by: Dasgupta, S., et al.
Published: (2013)