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Community detection in graphs (Alex Levin, PyData TLV - Oct 21)
Detect communities in graphs using bipartite models, graph theory, and mathematical modeling to analyze complex networks, identify patterns, and detect anomalies.
- Community detection can be achieved by modeling the similarity between nodes and using a bipartite graph.
- The affiliation graph model (AGM) can be used to describe overlapping communities.
- Modularity is a measure of the quality of community detection, calculated as the difference between the number of edges within a community and the number of edges expected by chance.
- The Levene algorithm is a method for detecting non-overlapping communities, but is not suitable for overlapping communities.
- The AGM model can be used to generate a graph that is similar to the original graph.
- The Louvain algorithm is a method for detecting overlapping communities.
- Community detection can be applied to social networks, such as online communities or networks of friends.
- Graph theory and mathematical modeling can be used to analyze and understand complex networks.
- Gradient descent can be used to optimize the AGM model and find the best community partition.
- Modularity is a non-linear measure, and the AGM model can be used to optimize it.
- The AGM model can be used to generate a graph that is similar to the original graph, and to detect overlapping communities.
- Community detection can be used to identify malicious networks and to detect anomalies in complex systems.
- The AGM model is a flexible model that can be used to describe overlapping communities.
- The Louvain algorithm is a fast and efficient method for detecting communities, but is not suitable for overlapping communities.
- Modularity is a measure of the quality of community detection, and can be used to evaluate the performance of community detection algorithms.
- Community detection can be used to identify patterns and structures in complex networks.
- The AGM model can be used to generate a graph that is similar to the original graph, and to detect overlapping communities.
- Graph theory and mathematical modeling can be used to analyze and understand complex networks.
- Community detection can be used to identify malicious networks and to detect anomalies in complex systems.
- The Louvain algorithm is a method for detecting non-overlapping communities, but is not suitable for overlapping communities.