Quick detection of top-k personalized PageRank lists

Avrachenkov, Konstatin and Litvak, Nelly and Nemirovsky, Danil and Smirnova, Elena and Sokol, Marina (2011) Quick detection of top-k personalized PageRank lists. In: 8th International Workshop on Algorithms and Models for the Web Graph, WAW 2011, 27-29 May 2011, Atlanta, GA, USA.

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Abstract:	We study a problem of quick detection of top-k Personalized PageRank (PPR) lists. This problem has a number of important applications such as finding local cuts in large graphs, estimation of similarity distance and person name disambiguation. We argue that two observations are important when finding top-k PPR lists. Firstly, it is crucial that we detect fast the top-k most important neighbors of a node, while the exact order in the top-k list and the exact values of PPR are by far not so crucial. Secondly, by allowing a small number of “wrong” elements in top-k lists, we achieve great computational savings, in fact, without degrading the quality of the results. Based on these ideas, we propose Monte Carlo methods for quick detection of top-k PPR lists. We demonstrate the effectiveness of these methods on the Web and Wikipedia graphs, provide performance evaluation and supply stopping criteria.
Item Type:	Conference or Workshop Item
Copyright:	© 2011 Springer
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Stochastic Operations Research (SOR)
Link to this item:	http://purl.utwente.nl/publications/78883
Official URL:	http://dx.doi.org/10.1007/978-3-642-21286-4_5
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