DEMON: Uncovering Overlapping Communities with a Local-First Approach
- Day - Time: 24 June 2013, h.11:00
- Place: Area della Ricerca CNR di Pisa - Room: C-29
Speakers
Referent
Abstract
Community discovery in complex networks is an interesting problem with a number of applications, especially in the knowledge extraction task in social and information networks. However, many large networks often lack a particular community organization at a global level. In these cases, traditional graph partitioning algorithms fail to let the latent knowledge embedded in modular structure emerge, because they impose a top-down global view of a network. DEMON is a simple local-first approach to community discovery, able to unveil the modular organization of real complex networks. This is achieved by democratically letting each node vote for the communities it sees surrounding it in its limited view of the global system, i.e. its ego neighborhood, using a label propagation algorithm; finally, the local communities are merged into a global collection.
NOTE: This seminar belongs to the series of seminars presented by the winners of the prize "Young researchers ISTI 2013". Giulio Rossetti placed second in the PhD student category
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