Label-dependent Feature Extraction in Social Networks for Node Classification

📝 Original Info

• Title: Label-dependent Feature Extraction in Social Networks for Node Classification
• ArXiv ID: 1303.0095
• Date: 2013-03-04
• Authors: Researchers from original ArXiv paper

📝 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.

💡 Deep Analysis

Deep Dive into Label-dependent Feature Extraction in Social Networks for Node Classification.

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.

📄 Full Content

Reference