12.1節 はじめに
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Data Mining: Concepts and Techniques | Han et al | 2022 | amazon | 1 |
12.2節 Webデータマイニング
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| DeepInf: Social Influence Prediction with Deep Learning | Qiu et al | 2018a | arxiv | 1 |
| Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media | Li and Goldwasser | 2019 | リンク | 2 |
| MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network | Wang et al | 2019a | arxiv | 3 |
| Using collaborative filtering to weave an information tapestry | Goldberg et al | 1992 | リンク | 4 |
| Recommender Systems | Resnick and Varian | 1997 | リンク | 5 |
| Eigentaste: A Constant Time Collaborative Filtering Algorithm | Goldberg et al | 2001 | リンク | 6 |
| Matrix Factorization Techniques for Recommender Systems | Koren et al | 2009 | 7 | |
| Neural Graph Collaborative Filtering | Wang et al | 2019h | arxiv | 8 |
| Graph Convolutional Matrix Completion | Berg et al | 2017 | arxiv | 9 |
| Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Ying et al | 2018a | arxiv | 10 |
| Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems | Wang et al | 2019b | arxiv | 11 |
| Knowledge Graph Convolutional Networks for Recommender Systems | Wang et al | 2019c | arxiv | 12 |
| KGAT: Knowledge Graph Attention Network for Recommendation | Wang et al | 2019g | arxiv | 13 |
| Graph Neural Networks for Social Recommendation | Fan et al | 2019 | arxiv | 14 |
| Learning Entity and Relation Embeddings for Knowledge Graph Completion | Lin et al | 2015 | リンク | 15 |
12.3節 都市データマイニング
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting | Yu et al | 2017 | arxiv | 1 |
| Attention Guided Graph Convolutional Networks for Relation Extraction | Guo et al | 2019 | arxiv | 2 |
| Traffic Flow Prediction via Spatial Temporal Graph Neural Network | Wang et al | 2020a | リンク | 3 |
| A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory | Qi et al | 2019 | リンク | 4 |
12.4節 サイバーセキュリティ・データマイニング
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Heterogeneous Graph Neural Networks for Malicious Account Detection | Liu et al | 2018b | arxiv | 1 |
| The spread of true and false news online | Vosoughi et al | 2018 | リンク | 2 |
| Fake News Detection on Social Media using Geometric Deep Learning | Monti et al | 2019 | arxiv | 3 |
12.6節 参考文献
| タイトル | 著者名 | 年 | リンク | 登場順 |
|---|---|---|---|---|
| Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media | Li and Goldwasser | 2019 | リンク | 1 |
| FdGars: Fraudster Detection via Graph Convolutional Networks in Online App Review System | Wang et al | 2019d | リンク | 2 |
| Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection | Liu et al | 2020 | arxiv | 3 |
| Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics | Weber et al | 2019 | arxiv | 4 |
| Supervised Community Detection with Line Graph Neural Networks | Chen et al | 2017 | arxiv | 5 |
| Overlapping Community Detection with Graph Neural Networks | Shchur and Günnemann | 2019 | arxiv | 6 |
| One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks | Wang et al | 2020b | arxiv | 7 |
| Anomaly Detection using Graph Neural Networks | Chaudhary et al | 2019 | リンク | 8 |