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. © 2010 Springer-Verlag.
CITATION STYLE
Kajdanowicz, T., Kazienko, P., & Doskocz, P. (2010). Label-dependent feature extraction in social networks for node classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6430 LNCS, pp. 89–102). https://doi.org/10.1007/978-3-642-16567-2_7
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