Label-dependent Feature Extraction in Social Networks for Node Classification
提出了一种基于社会网络特征提取的网络内分类方法。该方法提供了结合网络结构信息和分配给节点的类标签来计算的新特性。研究了不同特征对分类性能的影响。在真实数据上的实验表明，该方法生成的特征可以显著提高分类精度。 Introduction 有一些应用和研究方法，特别是与社交网络相关的应用和研究方法，能够产生相互连接的对象标签之间依赖的数据，称为关系自相关。根据这些连接，应该向分类过程中添加额外的输入
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相关文章
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