SEDGN: Sequence enhanced denoising graph neural network for session-based recommendation
C Zhang, W Zheng, Q Liu, J Nie, H Zhang - Expert Systems with …, 2022 - Elsevier
Session-based recommendation, which aims at predicting subsequent user actions based
on anonymous sessions, plays a significant role in many online services. Based on the …
on anonymous sessions, plays a significant role in many online services. Based on the …
DSGNN: A dynamic and static intentions integrated graph neural network for session-based recommendation
C Zhang, Q Liu, Z Zhang - Neurocomputing, 2022 - Elsevier
Session-based recommendation, which aims to predict subsequent user actions based on
anonymous sessions, plays a significant role in many online services. Existing methods …
anonymous sessions, plays a significant role in many online services. Existing methods …
Graph neural networks with global noise filtering for session-based recommendation
L Feng, Y Cai, E Wei, J Li - Neurocomputing, 2022 - Elsevier
Session-based recommendation leverages anonymous sessions to predict which item a
user is most likely to click on next. While previous approaches capture items-transition …
user is most likely to click on next. While previous approaches capture items-transition …
Dynamic global structure enhanced multi-channel graph neural network for session-based recommendation
Session-based recommendation is a challenging task, which aims at making
recommendation for anonymous users based on in-session data, ie short-term interaction …
recommendation for anonymous users based on in-session data, ie short-term interaction …
Combine temporal information in session-based recommendation with graph neural networks
Q Chen, F Jiang, X Guo, J Chen, K Sha… - Expert Systems with …, 2024 - Elsevier
With the rapid growth of Internet data, recommendation systems have become the basic
technology to alleviate information overload. The session-based recommendation (SBR) is a …
technology to alleviate information overload. The session-based recommendation (SBR) is a …
Contrastive multi-level graph neural networks for session-based recommendation
Session-based recommendation (SBR) aims to predict the next item at a certain time point
based on anonymous user behavior sequences. Existing methods typically model session …
based on anonymous user behavior sequences. Existing methods typically model session …
Dynamic graph learning for session-based recommendation
Z Pan, W Chen, H Chen - Mathematics, 2021 - mdpi.com
Session-based recommendation (SBRS) aims to make recommendations for users merely
based on the ongoing session. Existing GNN-based methods achieve satisfactory …
based on the ongoing session. Existing GNN-based methods achieve satisfactory …
Personalized graph neural networks with attention mechanism for session-aware recommendation
The problem of session-aware recommendation aims to predict users' next click based on
their current session and historical sessions. Existing session-aware recommendation …
their current session and historical sessions. Existing session-aware recommendation …
TAGNN: Target attentive graph neural networks for session-based recommendation
Session-based recommendation nowadays plays a vital role in many websites, which aims
to predict users' actions based on anonymous sessions. There have emerged many studies …
to predict users' actions based on anonymous sessions. There have emerged many studies …
Session-based recommendation with heterogeneous graph neural networks
L Xu, WD Xi, CD Wang - 2021 International Joint Conference …, 2021 - ieeexplore.ieee.org
The aim of session-based recommendation is to predict the next-clicked item based on the
anonymous behavior sequence. The existing works on session-based recommendation …
anonymous behavior sequence. The existing works on session-based recommendation …