Community discovery by propagating local and global information based on the MapReduce model
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Summary
Three strategies, namely, localizing propagation of affinity messages, relaxing self-exemplar constraints, and hierarchical processing, are employed in the algorithm to achieve reasonable time and space complexities in social networks.
- Type
- article
- Published
- 2015-12-01
- Cited by
- 70
- References
- 51
- OpenAlex
- https://openalex.org/W818837996
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:42717224
Keywords
Computer science, SPARK (programming language), Centrality, Cluster analysis, Big data
References
- Hadoop: The Definitive Guide
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- HaLoop
- Functional cartography of complex metabolic networks
- Enhancing community detection using a network weighting strategy
- Detecting Local Communities within a Large Scale Social Network Using Mapreduce
- Comparison of the Efficiency of MapReduce and Bulk Synchronous Parallel Approaches to Large Network Processing
- A bridging model for parallel computation
- Finding community structure in very large networks.
- Laplacian centrality: A new centrality measure for weighted networks
- Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks
- LI-MR: A Local Iteration Map/Reduce Model and Its Application to Mine Community Structure in Large-Scale Networks
- PSCAN: A Parallel Structural Clustering Algorithm for Big Networks in MapReduce
- Finding and evaluating community structure in networks.
Cited by
- A social community detection algorithm based on parallel grey label propagation
- Voting-based instance selection from large data sets with MapReduce and random weight networks
- Affinity Propagation Clustering Using Path Based Similarity
- An Empirical Comparison of Algorithms to Find Communities in Directed Graphs and Their Application in Web Data Analytics
- An Agricultural Service Oriented Information Discovery Technology for Internet of Things
- Generation of power-law networks by employing various attachment schemes: Structural properties emulating real world networks
- Distributed Holistic Clustering on Linked Data
- Optimization and Application of Clustering Algorithm in Community Discovery
- Exploring Big Data Clustering Algorithms for Internet of Things Applications
- Local Community Detection With the Dynamic Membership Function
- Differentially private graph-link analysis based social recommendation
- Multiple Relevant Feature Ensemble Selection Based on Multilayer Co-Evolutionary Consensus MapReduce
- Reliability Analysis of IoT Networks with Community Structures
- CASS: A distributed network clustering algorithm based on structure similarity for large-scale network
- A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things
- Finding patterns in the degree distribution of real-world complex networks: going beyond power law
- Dynamic community detection method based on an improved evolutionary matrix
- Distributed Centrality Analysis of Social Network Data Using MapReduce
- Using Cache Optimization Method to Reduce Network Traffic in Communication Systems Based on Cloud Computing
- User interaction-oriented community detection based on cascading analysis
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