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GNN for Recommender Systems

Type
Resource
Language
πŸ‡°πŸ‡·
Latest checked date
2023/01/20
Status
Done
1 more property

Introduction

λ§Žμ€ κΈ°μ—…μ—μ„œ ν•„μš”λ‘œ ν•˜κ³ , μ‹€μ œλ‘œ λ‹€μ–‘ν•œ 기술이 개발되고 적용되고 μžˆλŠ” Recommender system에 Graph Neural Network 이 μ–΄λ–»κ²Œ 적용되고 μžˆλŠ”μ§€ μ •λ¦¬ν•œ νŽ˜μ΄μ§€μž…λ‹ˆλ‹€.
ν•¨κ»˜ μŠ€ν„°λ””ν•˜μ‹œλŠ” λΆ„λ“€κ³Ό κ³΅λ™μž‘μ—… ν•˜μ˜€μŠ΅λ‹ˆλ‹€.

Survey paper

Graph Neural Networks in Recommender Systems: A Survey
With the explosive growth of online information, recommender systems play a key role to alleviate such information overload. Due to the important application value of recommender systems, there have always been emerging works in this field. In recommender systems, the main challenge is to learn the effective user/item representations from their interactions and side information (if any).
https://arxiv.org/abs/2011.02260
Search
Name
Person
λΉ„κ³ 
1. Introduction
Open
λͺ¨λ‘ 같이 읽기
2. Backgrounds and Categorization
Open
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
3. User-Item Collaborative Filtering
Open
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
4. Sequential Recommendation
Open
h2o0318@snu.ac.kr
μ„±ν›ˆ
5. Social Recommendation
Open
Taebaek
Taebaek
6. Knowledge Graph Based Recommendation
Open
Taebaek
Taebaek
7. Other Tasks
Open
κ΅¬μ •ν˜„
κ΅¬μ •ν˜„
8. Datasets, Evaluation Metrics and Applications
Open
κ΅¬μ •ν˜„
κ΅¬μ •ν˜„
9. Future Research Directions and Open Issue
Open
ν•¨μŠΉμš° Β­
ν•¨μŠΉμš° Β­
10. Conclusion
Open
ν•¨μŠΉμš° Β­
ν•¨μŠΉμš° Β­

GNN for Recommender Systems

Search
Name of Article
Person
Progress
Journal / Conference
Year
URL
λΉ„κ³ 
Files & media
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Open
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
Done
AAAI
2021
STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation
Open
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
Not started
0
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Open
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
λ°•μ„±μ—° / 학생 / κ±΄μ„€ν™˜κ²½κ³΅ν•™λΆ€ Β­
Not started
0
Neighborhood-aware Scalable Temporal Network Representation Learning
Open
κ΅¬μ •ν˜„
κ΅¬μ •ν˜„
Done
LoG
2022
https://arxiv.org/abs/2209.01084
Link Prediction Based on Graph Neural Networks
Open
κ΅¬μ •ν˜„
κ΅¬μ •ν˜„
Not started
NeurIPS
2018
https://arxiv.org/abs/1802.09691
How Attentive are Graph Attention Networks?
Open
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
Done
ICLR
2022
https://arxiv.org/pdf/2105.14491v3.pdf
Star Graph Neural Networks for Session-based Recommendation
Open
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
Not started
CIKM
2020
https://staff.fnwi.uva.nl/m.derijke/wp-content/papercite-data/pdf/pan-2020-star.pdf
Global Context Enhanced Graph Neural Networks for Session-based Recommendation (GCE-GNN)
Open
h2o0318@snu.ac.kr
μ„±ν›ˆ
Not started
SIGIR
2021
https://arxiv.org/pdf/2106.05081.pdf
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation (HG-GNN)
Open
h2o0318@snu.ac.kr
μ„±ν›ˆ
In progress
WSDM
2022
https://arxiv.org/pdf/2107.03813.pdf
Self-supervised Graph Learning for Recommendation
Open
h2o0318@snu.ac.kr
μ„±ν›ˆ
Done
SIGIR
2021
https://arxiv.org/pdf/2010.10783.pdf
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation
Open
Taebaek
Taebaek
Not started
AAAI
2020
https://arxiv.org/pdf/2004.12118.pdf
Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network
Open
Taebaek
Taebaek
Not started
WSDM
2022
https://dl.acm.org/doi/abs/10.1145/3488560.3498414
Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network.pdf
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
Open
ν•¨μŠΉμš° Β­
ν•¨μŠΉμš° Β­
Done
AAAI
2021
https://ojs.aaai.org/index.php/AAAI/article/view/16578
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation.pdf
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
Open
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
μ΅œμ„±ν™˜ / 학생 / 컴퓨터곡학뢀 Β­
Done
CIKM
2021
https://arxiv.org/pdf/2110.15114v1.pdf