Average Distance Queries through Weighted Samples in Graphs and Metric Spaces: High Scalability with Tight Statistical Guarantees

@inproceedings{Chechik2015AverageDQ,
  title={Average Distance Queries through Weighted Samples in Graphs and Metric Spaces: High Scalability with Tight Statistical Guarantees},
  author={Shiri Chechik and Edith Cohen and Haim Kaplan},
  booktitle={APPROX-RANDOM},
  year={2015}
}
The average distance from a node to all other nodes in a graph, or from a query point in a metric space to a set of points, is a fundamental quantity in data analysis . The inverse of the average distance, known as the (classic) closeness centrality of a node, is a popular importance measure in the study of social networks. We show that the average distance (and hence the ce ntrality) for all nodes in a network can be estimated in timeO(ǫm logn), wheren andm are the number of nodes and edges… CONTINUE READING
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