CoLink: An Unsupervised Framework for User Identity Linkage
CoLink: An Unsupervised Framework for User Identity Linkage AAAI2018 摘要 在本文中，我们提出了一个通用的无监督框架CoLink来解决UIL问题。社交网络的个人资料数据可以自然地分为两个独立的视图:属性和关系，这满足了协同训练算法(Blum和Mitchell)的要求1998)。CoLink使用了两个独立的模型，一个基于属性的模型和
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相关文章
- 1. Unsupervised User Identity Linkage via Factoid Embedding 阅读笔记
- 2. Graph Neural Networks for User Identity Linkage 2019 论文阅读笔记
- 3. DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data 阅读笔记
- 4. ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation 详解
- 5. Domain Adaptation for Object Recognition: An Unsupervised Approach
- 6. An Unsupervised Autoregressive Model for Speech Representation Learning
- 7. Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
- 8. 04 PointAugment: an Auto-Augmentation Framework for Point Cloud Classification
- 9. GraphGen: An FPGA Framework for Vertex-Centric Graph Computation
- 10. An empty identity is not valid when signing a binary for the product type 'Dynamic Library'