HotChoc的博客

Graph Neural Networks in Recommender Systems - A Survey LINK: https://arxiv.org/abs/2011.02260 CLASSIFICATION: RECOMMENDER-SYSTEM, GNN, SURVEY YEAR: Submitted on 4 Nov 2020 FROM: arXiv

Gemini: A Novel and Universal Heterogeneous Graph Information Fusing Framework for Online Recommendations LINK: https://doi.org/10.1145/3394486.3403388 CLASSIFICATION: RECOMMENDER-SYSTEM, HETEROGENEOUS NETWORK, GCN YEAR: Submitted on Aug 2020 FROM:

Graph Neural Networks for Social Recommendation LINK: https://arxiv.org/abs/1902.07243 CLASSIFICATION: RECOMMENDER-SYSTEM, HETEROGENEOUS NETWORK, GCN YEAR: Submitted on 19 Feb 2019 (v1), last revised 23 Nov 2019 (this version, v2) FROM: WWW 2019

Reviews Meet Graphs

IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation LINK: https://arxiv.org/abs/1907.12377 CLASSIFICATION: RECOMMENDER-SYSTEM, HETEROGENEOUS NETWORK, GCN YEAR: Submitted on 24 Jul 2019 FROM: KDD 2019

Graph Attention Networks LINK: https://arxiv.org/abs/1710.10903 CLASSIFICATION: SPATIAL-BASED GCN YEAR: Submitted on 30 Oct 2017 (v1), last revised 4 Feb 2018 (this version, v3) FROM: ICLR 2018 WHAT PROBLEM TO SOLVE: To overcome the limitations o

Graph Convolutional Neural Networks for Web-Scale Recommender Systems LINK: https://arxiv.org/abs/1806.01973 CLASSIFICATION: RECOMMENDER-SYSTEM, GCN YEAR: Submitted on 6 Jun 2018 FROM: KDD 201...

Inductive Representation Learning on Large Graphs LINK: https://arxiv.org/abs/1706.02216 CLASSIFICATION: SPATAIL-BASED GCN YEAR: Submitted on 7 Jun 2017 (v1), last revised 10 Sep 2018 (this vers...

A Comprehensive Survey on Graph Neural Networks LINK: https://arxiv.org/abs/1901.00596 CLASSIFICATION: GNN, SURVEY YEAR: 2019 FROM: ArXivID:1901.00596 WHAT PROBLEM TO SOLVE: Existing surveys...