Label-dependent Feature Extraction in Social Networks for Node Classification
arXiv:1303.0095 · doi:10.1007/978-3-642-16567-2_7
Abstract
A new method of feature extraction in the social network for within-network classification is proposed in the paper. The method provides new features calculated by combination of both: network structure information and class labels assigned to nodes. The influence of various features on classification performance has also been studied. The experiments on real-world data have shown that features created owing to the proposed method can lead to significant improvement of classification accuracy.
feature extraction, label-dependent features, classification, social network analysis, AMD social network