Complete graph reconstruction from partial information

Abstract

Networks, biological molecules, neural structures can be represented as graphs. Data processing and storage of such structures with millions of nodes is very bulky. Thus, we derive important properties and synthesize a technique to regenerate a graph from partial information about the graph with minimum data and high fidelity. This will impact the way we store and operate on network data and opens new possibilities in areas such as chemistry, social networks, neural networks and the ever evolving Internet.