Community Discovery in Complex Network Big Data

Author:

Ji Qingbin1ORCID

Affiliation:

1. North University of China, China

Abstract

Community structure is a topological property of complex networks, and community discovery is the foundation of community structure study. Community discovery technology could serve as an important tool to provide strong theoretical support for big data analysis, research, and application, thereby aiding people's prediction and decision-making behavior. The authors aim to provide a systematic review of the fundamental and application of community structure theory in complex network big data studies, with a particular focus on the promoting role of community discovery in specific re-search fields. This chapter mainly consists of three parts: 1) first introduced the theoretical basis of community discovery, 2) second introduced community discovery methods categorizing from technology, and 3) last introduced new tasks and application of community discovery in big data. By reading this chapter, readers should gain a comprehensive understanding of how to introduce community thinking in big data analysis and contribute to improving decision-making ability.

Publisher

IGI Global

Reference62 articles.

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5. Chien, E., Lin, C. Y., & Wang, I. H. (2018). Community detection in hypergraphs: optimal statistical limit and efficient algorithms. International Conference on Artificial Intelligence and Statistics. https://proceedings.mlr.press/v84/chien18a/chien18a-supp.pdf

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