论文User identification across online social networks in practice: Pitfalls and solutions研究总结
文章通过社会网络的官方应用程序编程接口（API）的公共属性获得数据集，提出了构建超越常规随机选择的负面实例的不同方法，以研究每种方法在训练分类器中的有效性。为了评估不同分类器的健壮性，建立了两个具有不同层次的区别的测试集。通过匹配从Google+、Facebook和Twitter收集的个人资料，在真实情况下衡量这种方法的有效性。 Keywords：Classification; online so
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相关文章
- 1. 【论文总结】Aligning users across social networks using network embedding
- 2. SynchroTrap：Uncovering Large Groups of Active Malicious Accounts in Online Social Networks（论文笔记）
- 3. SybilWalk：Random Walk based Fake Account Detection in Online Social Networks论文笔记
- 4. Friendship and Mobility: User Movement In Location-Based Social Networks 阅读报告
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- 6. 论文翻译：On Finding Socially Tenuous Groups for Online Social Networks
- 7. 500 Data Structures and Algorithms practice problems and their solutions
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