Influence Neighbourhoods in CiteSeer: A Case Study

We are interested in using purely network-based techniques to assist in matching instances across databases that can be represented as complex networks. In particular we are interested in the individuality of the influence neighbourhood of a node (the sub graph induced by its in-neighbours) in a directed network. We derive a paper citation network from the archived Cite Seer database and use this network as a case study of influence neighbourhoods. We show that papers can reliably be distinguished by their influence neighbourhoods.

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