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Network Pruning For Scaling Dynamic Community Detection, Gaurav Ghosh
Network Pruning For Scaling Dynamic Community Detection, Gaurav Ghosh
Legacy Theses & Dissertations (2009 - 2024)
Local community detection is an important tool for the analysis of networks of different genres. The goal is to identify only the best communities in a network instance as opposed to computing a partitioning of the whole network. The majority of the work on local community detection has focused on static networks with less attention on networks that evolve over time. Given a trace of temporal interaction among nodes in a network, how can we detect a period of high interaction for a specific group of nodes? To help temporal community detection with the need to search in the time …
Synchronous Subgraphs In Networks, Navita Jain
Synchronous Subgraphs In Networks, Navita Jain
Legacy Theses & Dissertations (2009 - 2024)
Community detection is a central problem in network analysis. The majority of existing work defines communities as subsets of nodes that are structurally well-connected and isolated from the rest of the network. Apart from their underlying connectivity, nodes in real-world networks exhibit temporal activity: user posts in social networks, browsing activity on web pages and neuron activations in brain networks to name a few. While edges encode potential for community interactions, participation in the community can be quantified by synchronized member activity. Given both the network structure and individual node activity, how can we detect communities that are both well-connected …