CGS: Configurable Graph Summarization with Bounded Neighborhood Loss and Query Support
Given a large graph, how to generate a compact summary graph that is configurable by the user and supports multiple graph queries with either no loss or with high accuracy? The ever growing size of graph datasets makes the above question on graph summarization very pertinent. Although, there are several approaches, there does not exist a configurable graph summarization method that offers high compression along with support for multiple graph queries on the summary graph with high accuracy, and allows the user to configure the summarization based on: (1) lossless or lossy summarization, (2) amount of tolerable neighborhood loss, (3) the type of loss it can tolerate, in terms of false posi...
| Authors | Shubhadip Mitra, Sona Elza Simon, C Oswald et al. |
|---|---|
| Primary category | cs.DS |
| Published | 13 July 2026 |
| Last updated at source | 13 July 2026 |
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