Memory-augmented meta-learning on meta-path for fast adaptation cold-start recommendation

Memory-augmented meta-learning on meta-path for fast adaptation cold-start recommendation

Personalised recommendation is a difficult problem that has received a lot of attention to academia and industry. Because of the sparse user–item interaction, cold-start recommendation has been a particularly difficult problem. Some efforts have been made to solve the cold-start problem by using mod...

Full description

Saved in:
Bibliographic Details
Main Authors: Tianyuan Li, Xin Su, Wei Liu, Wei Liang, Meng-Yen Hsieh, Zhuhui Chen, XuChong Liu, Hong Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Connection Science
Subjects:
cold-start recommendation
memory-augmented
meta-path
meta-learning
Online Access:http://dx.doi.org/10.1080/09540091.2021.1996537
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://dx.doi.org/10.1080/09540091.2021.1996537

Similar Items