From Santa Fe Institute Events Wiki
Statistical Inference for Complex Networks Workshop, December 3-5, 2008, Santa Fe NM
Lise Getoor (homepage)
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.