A new method of feature extraction in the social network for withinnetwork 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 realworld data have shown that features created owing to the proposed method can lead to significant improvement of classification accuracy.
In these approaches, both network structure information and node class labels are combined to provide new features to improve classification REF .
Label-dependent Feature Extraction in Social Networks for Node Classification
Kajdanowicz T., Kazienko P., Doskocz P.: Label-dependent Feature Extraction in Social Networks for Node Classification. Lecture Notes in Artificial Intelligence LNAI 6430, Springer, 2010, pp. 89-102
Computer Science