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Incremental Graph Clustering in Parallel

DescriptionWe develop a distributed memory graph clustering algorithm to find clusters in a graph where new nodes and edges are being added incrementally. At each stage of the algorithm, we maintain a summary of the clustered graph computed from all incremental batches received thus far. As we receive a new batch of nodes and edges, we cluster the new graph and merge new clusters with the previous summary clusters. We use sparse linear algebra to perform these operations. Our algorithm would make it possible to find clusters in very large graphs for which regular graph clustering algorithms could not run due to computation/communication bottlenecks.

Author

Md Taufique Hussain

Indiana University

Event Type

ACM Student Research Competition: Graduate Poster

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Doctoral Showcase

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Scientific Visualization & Data Analytics Showcase