Local Computation of PageRank Contributions

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Local Computation of PageRank Contributions
Motivated by the problem of detecting link-spam, we consider the following graph-theoretic primitive: Given a webgraph G, a vertex v in G, and a parameter δ ∈ (0, 1), compute the set of all vertices that contribute to v at least a δ fraction of v’s PageRank. We call this set the δ-contributing set of v. To this end, we define the contribution vector of v to be the vector whose entries measure the contributions of every vertex to the PageRank of v. A local algorithm is one that produces a solution by adaptively examining only a small portion of the input graph near a specified vertex. We give an efficient local algorithm that computes an -approximation of the contribution vector for a given vertex by adaptively examining O(1/ ) vertices. Using this algorithm, we give a local approximation algorithm for the primitive defined above. Specifically, we give an algorithm that returns a set containing the δcontributing set of v and at most O(1/δ) vertices from the δ/2-contributin...
Reid Andersen, Christian Borgs, Jennifer T. Chayes
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where WAW
Authors Reid Andersen, Christian Borgs, Jennifer T. Chayes, John E. Hopcroft, Vahab S. Mirrokni, Shang-Hua Teng
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