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Statistical Inference for Complex Networks Workshop, December 3-5, 2008, Santa Fe NM

Organizers: Aaron Clauset (SFI) and Cris Moore (UNM & SFI)

Lise Getoor (homepage)

Graph Identification

Graph identification refers to methods that transform observational data described as a noisy, incomplete input graph into an inferred "clean" output graph or network. Examples include inferring organizational hierarchies from communication data, identifying gene regulatory networks from protein-protein interactions, and understanding visual scenes based on inferred relationships among image parts. The key processes in graph identification are: entity resolution, link prediction, and collective classification. I will overview algorithms for these tasks, discuss the need for integrating the results to solve the overall problem collectively.