Benchmark current performance on public datasets about cassovary HOT 3 CLOSED

Hi Pankaj, this issue is quite old, is it still available?

I see your global pagerank implementation in algorithms package. I guess I should start with coding personalized pagerank. Am I correct, that the only difference between personalized and the global one is the non-uniform probabilities vector for jumps? In your implementation it means a an array of dampingAmount instead of one value. This should be passed as a parameter to the algorithm. Am I right?

So shouldn't I generalize the global one? For example by adding optional parameter Function1[Int, Double](default _ => 1) to the PageRankParams?

from cassovary.

Yes, this is still valid.
Personalized pagerank already exists. See method calculatePersonalizedReputation(…) in https://github.com/twitter/cassovary/blob/master/src/main/scala/com/twitter/cassovary/graph/GraphUtils.scala#L136

from cassovary.

This should be closed.

from cassovary.