WGIN: A Session-Based Recommendation Model Considering the Repeated Link Effect

WGIN: A Session-Based Recommendation Model Considering the Repeated Link Effect

Session-based recommendation systems have high application value. Determining how to make better use of anonymous user sessions to recommend items of interest is a considerable challenge for current recommendation systems. Existing research has mainly focused on sequential session patterns; however,...

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Bibliographic Details
Main Authors: Zhenyu Yang, Hao Wang, Mingge Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Graph neural network
user preferences
transformer
attention mechanism
session-based recommendation
Online Access:https://ieeexplore.ieee.org/document/9274330/

Internet

https://ieeexplore.ieee.org/document/9274330/

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