title: Pagerank formula for graph with weighted edges(sequential or BSP )
body: <p>Pagerank algorithms (that I know) assume that the edges do not have weights. So the standard formula is: </p>
  
  <pre><code>PR(A) = (1 - d)/N + d*\sigma PR(E)/L(E)
  </code></pre>
  
  <p>where L(E) is the number of outgoing links of page E where E is each page that points to page A.</p>
  
  <p>As you can see here, the weights of the edges coming in to A are not considered in the formula.</p>
  
  <p>Two questions:</p>
  
  <p>a) What would be the adjusted formula if we considered the weight of each edge coming into A, assuming that higher the weight the better(networkx package in python does consider weighted edges, but the code is much more involved than the above formula and I would prefer checking if there was a simpler solution)</p>
  
  <p>b) I actually want this for a BSP Pregel like framework. There is an <a href="http://spark-project.org/docs/latest/bagel-programming-guide.html" rel="nofollow" title="BSP Pregel style implementation">BSP Pregel style implementation</a> but as you can see, it does not consider the weights on the edge. If you can suggest one, that would be great</p>