An improved cross-domain sequential recommendation model based on intra-domain and inter-domain contrastive learning

An improved cross-domain sequential recommendation model based on intra-domain and inter-domain contrastive learning

Abstract Cross-domain recommendation aims to integrate data from multiple domains and introduce information from source domains, thereby achieving good recommendations on the target domain. Recently, contrastive learning has been introduced into the cross-domain recommendations and has obtained some...

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Bibliographic Details
Main Authors: Jianjun Ni, Tong Shen, Yonghao Zhao, Guangyi Tang, Yang Gu
Format: Article
Language:English
Published: Springer 2024-08-01
Series:Complex & Intelligent Systems
Subjects:
Cross-domain recommendation
Contrastive learning
Bias problem
Sequential interaction
Online Access:https://doi.org/10.1007/s40747-024-01590-1

Internet

https://doi.org/10.1007/s40747-024-01590-1

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