Personalized Pagerank

From TrustLet, a free, collaborative project for collecting and analyzing information about trust metrics.

T. Haveliwala, S. Kamvar, and G. Jeh. An analytical comparison of approaches to personalizing pagerank, 2003. Technical report, Stanford University, 2003.

But also Trust Management for the Semantic Web by Matthew Richardson, Rakesh Agrawal, and Pedro Domingos. Imagine a random knowledge-surfer hopping from user to user in search of beliefs. At each step, the surfer probabilistically selects a neighbor to jump to according to the current user’s distribution of trusts. (…) Further, choosing which user to jump to, the random surfer will, with probability delta (in [0,1]) ignore the trusts and instead jump directly back to the original user, i.

The intuition is that instead of jumping to some random walk with a certain probability during the random walk, the walker jumps with a higher probability to the original node from which trust started and for which we want to personalize the reputation computation.

This article is a stub. You can help by expanding it.