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The paper is referring to within-network classification problem. A new method for feature extraction is proposed in the paper. New features are obtained by combination of network structure information and class labels assigned to nodes. The influence of various features on classification performance has also been studied in the paper. The experiments based on real-world data have shown that the proposed method provides with features leading to significant improvement of classification accuracy.