DeepFusion: Fusing User-Generated Content and Item Raw Content towards Personalized Product Recommendation
Personalized recommender systems, as effective approaches for alleviating information overload, have received substantial attention in the last decade. Learning effective latent factors plays the most important role in recommendation methods. Several recent works extracted latent factors from user-g...
Saved in:
Main Authors: | Mingxin Gan, Hang Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/4780191 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid Movie Recommendation System With User Partitioning and Log Likelihood Content Comparison
by: Yongmao Yang, et al.
Published: (2025-01-01) -
MONITORING OF CALCIUM CONTENT OF RAW COW MILK
by: Ye. S. Kandinskaya, et al.
Published: (2019-04-01) -
Recognition model for major depressive disorder in Arabic user-generated content
by: Esraa M. Rabie, et al.
Published: (2025-01-01) -
The effect of user-generated content on tourist behavior: the mediating role of destination image
by: María del Carmen Hidalgo Alcázar, et al.
Published: (2014-01-01) -
A proposal for measuring hotels’ managerial responses to User-Generated-Content Reviews
by: Javier Perez-Aranda, et al.
Published: (2018-01-01)