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CORR
2010
Springer

Monte Carlo Methods for Top-k Personalized PageRank Lists and Name Disambiguation

11 years 4 months ago
Monte Carlo Methods for Top-k Personalized PageRank Lists and Name Disambiguation
We study a problem of quick detection of top-k Personalized PageRank lists. This problem has a number of important applications such as finding local cuts in large graphs, estimation of similarity distance and name disambiguation. In particular, we apply our results to construct efficient algorithms for the person name disambiguation problem. We argue that when finding top-k Personalized PageRank lists two observations are important. Firstly, it is crucial that we detect fast the top-k most important neighbours of a node, while the exact order in the top-k list as well as the exact values of PageRank are by far not so crucial. Secondly, a little number of wrong elements in top-k lists do not really degrade the quality of top-k lists, but it can lead to significant computational saving. Based on these two key observations we propose Monte Carlo methods for fast detection of top-k Personalized PageRank lists. We provide performance evaluation of the proposed methods and supply stoppi...
Konstantin Avrachenkov, Nelly Litvak, Danil Nemiro
Added 24 Jan 2011
Updated 24 Jan 2011
Type Journal
Year 2010
Where CORR
Authors Konstantin Avrachenkov, Nelly Litvak, Danil Nemirovsky, Elena Smirnova, Marina Sokol
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