Hiya,
I too am looking for a PageRank solution in GraphX where the probabilities
sum to 1.
I tried a few modifications, including division by the total number of
vertices in the first part of the equation, as well as trying to return full
rank instead of delta (though not correctly as evident fro
I see, thanks.
So to implement pagerank with damping factor divided by number of vertices:
Is it sufficient to modify initialMessage to
*val initialMessage = (resetProb / graph.vertices.count())/ (1.0 -
resetProb)*
instead of
*val initialMessage = resetProb / (1.0 - resetProb)*
and yield correc
At 2014-11-15 18:01:22 -0700, tom85 wrote:
> This line: val newPR = oldPR + (1.0 - resetProb) * msgSum
> makes no sense to me. Should it not be:
> val newPR = resetProb/graph.vertices.count() + (1.0 - resetProb) * msgSum
> ?
This is an unusual version of PageRank where the messages being passed
