Can this be done with a random projection? On Mon, Jul 25, 2011 at 4:59 AM, Sebastian Schelter (JIRA) <[email protected]>wrote:
> > [ > https://issues.apache.org/jira/browse/MAHOUT-773?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel] > > Sebastian Schelter updated MAHOUT-773: > -------------------------------------- > > Description: > I'll create an implementation of Random Walk with Restarts as described in > Kang, Tsourakakis, Faloutsos, "PEGASUS: A Peta-Scale Graph Mining System - > Implementation and Observations" > http://www.cs.cmu.edu/~christos/PUBLICATIONS/icdm09-pegasus.pdf > > The algorithm is a random walk similar to PageRank with the difference that > you start at and teleport to a certain node. The probabilities it computes > can be seen as a measure of proximity between the start node and a reached > node. To my knowledge RWR can be e.g used for link predicition in social > networks. > > I will try to create an implementation that is able to do several walks in > parallel and I will assume that a steadystate probability vector fits in > memory. > > I don't plan to use the implementation details from the paper but I'll > model the algorithm as an iterative multiplication between the adjacency > matrix of the graph and the matrix created from the steadystate probability > vectors for the vertices we compute the random walks for. > > was: > I'll create an implementation of Random Walk with Restarts as described in > Kang, Tsourakakis, Faloutsos, "PEGASUS: A Peta-Scale Graph Mining System - > Implementation and Observations" > http://www.cs.cmu.edu/~christos/PUBLICATIONS/icdm09-pegasus.pdf > > The algorithm is a random walk similar to PageRank with the difference that > you start at and teleport to a certain node. The probabilities it computes > can be seen as a measure of proximity between the start node and a reached > node. To my knowledge RWR can be e.g used for link predicition in social > networks. > > I will try to create an implementation that is able to do several walks in > parallel and I will assume that a steadystate probability vector fits in > memory. > > > > Implement Random Walk with Restarts > > ----------------------------------- > > > > Key: MAHOUT-773 > > URL: https://issues.apache.org/jira/browse/MAHOUT-773 > > Project: Mahout > > Issue Type: New Feature > > Components: Graph > > Affects Versions: 0.6 > > Reporter: Sebastian Schelter > > Assignee: Sebastian Schelter > > > > I'll create an implementation of Random Walk with Restarts as described > in Kang, Tsourakakis, Faloutsos, "PEGASUS: A Peta-Scale Graph Mining System > - Implementation and Observations" > http://www.cs.cmu.edu/~christos/PUBLICATIONS/icdm09-pegasus.pdf > > The algorithm is a random walk similar to PageRank with the difference > that you start at and teleport to a certain node. The probabilities it > computes can be seen as a measure of proximity between the start node and a > reached node. To my knowledge RWR can be e.g used for link predicition in > social networks. > > I will try to create an implementation that is able to do several walks > in parallel and I will assume that a steadystate probability vector fits in > memory. > > I don't plan to use the implementation details from the paper but I'll > model the algorithm as an iterative multiplication between the adjacency > matrix of the graph and the matrix created from the steadystate probability > vectors for the vertices we compute the random walks for. > > -- > This message is automatically generated by JIRA. > For more information on JIRA, see: http://www.atlassian.com/software/jira > > >
