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.
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Kajdanowicz, T., Kazienko, P., Doskocz, P. (2010). Label-Dependent Feature Extraction in Social Networks for Node Classification. In: Bolc, L., Makowski, M., Wierzbicki, A. (eds) Social Informatics. SocInfo 2010. Lecture Notes in Computer Science, vol 6430. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16567-2_7
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DOI: https://doi.org/10.1007/978-3-642-16567-2_7
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