【论文解读 CIKM 2018 | GEM】Heterogeneous Graph Neural Networks for Malicious Account Detection

时间 2020-12-30

标签论文 NE&GNN CIKM GNN HIN 恶意检测繁體版

原文原文链接

论文链接：https://arxiv.org/abs/2002.12307 来源：CIKM 2018 官方介绍：https://zhuanlan.zhihu.com/p/48243724 文章目录 1 摘要 2 介绍 3 预备知识 3.1 GNN 3.2 Node Embedding 4 提出的方法 4.1 数据分析 4.1.1 设备聚集 4.1.2 行为聚集 4.2 A Motivation:

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1. 【论文解读 CIKM 2018 | GEM】Heterogeneous Graph Neural Networks for Malicious Account Detection
2. 【论文解读 CIKM 2018 | JUST】Are Meta-Paths Necessary? Revisiting Heterogeneous Graph Embeddings
3. Heterogeneous Graph Neural Networks for Extractive Document Summarization
4. ACL2020 Heterogeneous Graph Neural Networks for Extractive Document Summarization
5. 论文阅读：Deep Neural Networks for Object Detection
6. 【论文笔记】Heterogeneous Graph Neural Networks for Extractive Document Summarization
7. 【论文解读 KDD 2019 | MEIRec】Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
8. 论文解读：Graph Convolutional Networks for Text Classifification
9. 科恩论文阅读：Semantic-Aware Neural Networks for Binary Code Similarity Detection
10. 《Heterogeneous Graph Attention Network》论文解读

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