PageRank

pagerank.lua

local function pagerank(mat, alpha, epsilon)
   alpha = alpha or 0.85
   epsilon = epsilon or 1.0e-5
   
   local state = torch.Tensor(mat:size(1)):fill(1.0 / mat:size(1))
   local p = mat:clone()
   local alpha_not = ((1.0 - alpha) / state:size(1))
   
   for i = 1, mat:size(1) do
      p[i]:div(mat[i]:sum() + 1.0e-6)
   end
   p = p:t():clone()
   while true do
      local prev = state:clone()
      local ip = torch.mv(p, prev)
      state:copy(ip:mul(alpha):add(alpha_not))
      local err = prev:dist(state, 1)
      if err < epsilon then
	 return state
      end
   end
end
local function pagerank_test()
   local sys = require 'sys'
   local mat = torch.Tensor(
      {
	 {0,0,1,1},
	 {0,0,1,1},
	 {1,1,0,0},
	 {0,1,1,0}
      })
   local alpha = 0.85
   local t = sys.clock()
   local rank = pagerank(mat, alpha)
   print(rank)
   print(sys.clock() - t)
end

--pagerank_test()

return pagerank