NAME
    Algorithm::PageRank::XS - Fast PageRank implementation

DESCRIPTION
    <Algorithm::PageRank> does some pagerank calculations, but it's slow and
    memory intensive. This was developed to compute pagerank on graphs with
    millions of arcs. It will not, however, scale up to quadrillions of arcs
    unless you have a lot of local memory. This is not a distributed
    algorithm.

SYNOPSYS
        use Algorithm::PageRank::XS;

        my $pr = Algorithm::PageRank::XS->new(alpha => 0.85);

        $pr->graph([
                  0 => 1,
                  0 => 2,
                  1 => 0,
                  2 => 1,
                  ]
                  );

        $pr->result();

        # This simple program takes up arcs and prints the ranks.

        use Algorithm::PageRank::XS;

        my $pr = Algorithm::PageRank::XS->new(alpha => 0.85);

        while (<>) {
            chomp;
            my ($from, to) = split(/\t/, $_);
            $pr->add_arc($from, $to);
        }

        while (my ($name, $rank) = each(%{$pr->result()})) {
            print("$name,$rank\n");
        }

CONSTRUCTORS
    new %PARAMS
        Create a new PageRank object. Parameters are: "alpha", "max_tries",
        and "convergence". "alpha" is the damping constant (how far from the
        true eigenvector you are. "max_tries" is the maximum number of
        iterations to run. "convergence" is how close our vectors must be
        before we say we are done.

    add_arc
        Add an arc to the pagerank object before running the computation.
        The actual values don't matter. So you can run:

            $pr->add_arc("Apple", "Orange");

        To mean that "Apple" links to "Orange".

    graph
        Add a graph, which is just an array of from, to combinations. This
        is equivalent to calling "add_arc" a bunch of times, but may be more
        convenient.

    results
        Compute the pagerank vector, and return it as a hash.

        Whatever you called the nodes when specifying the arcs will be the
        keys of this hash, where the values will be the vector (which should
        sum to 1).

PERFORMANCE
    This module is pretty fast. I ran this on a 1 million node set with 4.5
    million arcs in 57 seconds on my 32-bit 1.8GHz laptop. Let me know if
    you have any performance tips.

COPYRIGHT
    Copyright (C) 2008 by Michael Axiak <mike@axiak.net>

    This package is free software; you can redistribute it and/or modify it
    under the same terms as Perl itself