Absorbing random walk centrality

Our paper on absorbing random-walk centrality will be presented at ICDM next week. It is a joint work with Harry Mavroforakis and Aristides Gionis.

What is absorbing random-walk centrality (ARW-centrality)?

It is a measure that tells us how central one set of nodes (let’s call it C) is with respect to another set of nodes (let’s call it Q) in a graph. As an example, consider the graph shown in the figure below. In that graph, we use color to indicate the two sets of nodes — Q is shown in red and C is shown in blue. Continue reading

Finding similar neighborhoods across cities

By Geraud Le Falher, Michael Mathioudakis, and Aris Gionis

Our friend Oliver lives in London, where he works as a consultant for a big financial company. Occasionally, he takes a business trip to another major city, to seal a major deal, and make major buck for his boss. Of course, Oliver being Oliver, he always finds the time to enjoy whatever city he happens to be. When in London, he likes to suit up and hang out in Soho, a “predominantly fashionable district of upmarket restaurants.” He would like to do that also in Rome, where he’s flying to next week, but he doesn’t know much about that city. Where is the Soho of Rome? What neighborhood of Rome is most similar to Soho? Continue reading