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...

• Type: Conference
• Year: 2007
• Where: WAW
• Authors: Reid Andersen, Christian Borgs, Jennifer T. Chayes, John E. Hopcroft, Vahab S. Mirrokni, Shang-Hua Teng
• Keywords: Algorithms, Contribution Vector, Efficient Local Algorithm, Local Algorithm, WAW 2007