Analyzing graph structure via linear measurements

We initiate the study of graph sketching, i.e., algorithms that use a limited number of linear measurements of a graph to determine the properties of the graph. While a graph on n nodes is essentially O(n2 )-dimensional, we show the existence of a distribution over random projections into d-dimensional “sketch” space (d n2 ) such that the relevant properties of the original graph can be inferred from the sketch with high probability. Specifically, we show that:

• Type: Journal
• Year: 2012
• Where: SODA
• Authors: Kook Jin Ahn, Sudipto Guha, Andrew McGregor
• Keywords: Algorithms, Cally, Linear Measurements, Relevant Properties, SODA 2012