Louvain Clustering for Big Data Graph Visual Analytics
نویسندگان
چکیده
Challenges with using graphs to visualize extremely large entityrelationship datasets include visibility, usability and high degree nodes. Visual aggregation techniques, tools and easily tailorable components are needed that will support answering analytical questions with data description, characterization and interaction without loss of information. We present two case studies of prototype implementations of JavaScript browser-based visualization tools leveraging the Louvain clustering algorithm. Two “big data” datasets were used to test aggregation of large networks to reveal communities and answer analytical questions.
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تاریخ انتشار 2013