Sub-community Graph Retrieval from a Compressed Community Graph Using Graph Mining: New Perspective
Emerging Trends in Engineering Research and Technology Vol. 6,
Page 11-26
Abstract
Community detection and retrieval are the most relevant and important topics in graph mining. Hence it is treated as one of the important applications in the field of social network analysis. Community detection plays an important role in a large community graph by enabling and selecting the desired community’s sub-graph. This chapter proposes an algorithm that detects and extracts the desired sub-community graph from a compressed community graph for further analysis purposes. It presents both theoretical and experimental results with three benchmark social networks.
Keywords:
- Adjacency community matrix
- community graph
- cycle
- sub-adjacency matrix
- sub-community graph
- self-loops weights
How to Cite
Rao, B., & Mishra, S. (2020). Sub-community Graph Retrieval from a Compressed Community Graph Using Graph Mining: New Perspective. Emerging Trends in Engineering Research and Technology Vol. 6, 11-26. Retrieved from https://stm1.bookpi.org/index.php/etert-v6/article/view/1674
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