Community Detection Using Link Attribute-Based Classification

Jeongseon Kim, Soohwan Jeong, Sungsu Lim

http://doi.org/10.5626/JOK.2021.48.8.959

Attempts to discover knowledge through data are becoming gradually diversified to understand a fast and complex world. Graph data analysis, which models and analyzes correlated data as graphs, is drawing much attention as it is combined with the latest machine learning techniques. In this work, we propose a novel methodology for discovering graph community structures. We analyze similarity, curvature-based attributes to allow links existing inside and outside the community to have different attribute values, and exploit them to design and analyze algorithms that eliminate links that affect the community structure less to find better community structures on sparse graphs.