lectures.alex.balgavy.eu

Lecture notes from university.
git clone git://git.alex.balgavy.eu/lectures.alex.balgavy.eu.git
Log | Files | Refs | Submodules

The Web - PageRank.md (763B)


      1 +++
      2 title = 'The Web - PageRank'
      3 template = 'page-math.html'
      4 +++
      5 # The Web - PageRank
      6 uses hyperlinks to a page (indegrees) as criterion for importance of that page
      7 
      8 $rank(p) = (\frac{1-d}{n}+d) \times \sum_{\overrightarrow{<q, p> \in E}} \frac{rank(q)}{\delta_{out}(q)}$
      9 
     10 d ∈ [0,1) is a constant damping factor, Google probably uses 0.85
     11 
     12 $P[rank = k] \propto \frac{1}{k^{2.1}}$
     13 
     14 algorithm:
     15 1. V = {v1, v2, …, vn}. t=0. d ≈ 0.85
     16 2. PR(vi, t) = 1/n for all vi ∈ V
     17 3. for all vi, calculate:
     18     $PR(v_{i}, t+1) = \frac{1-d}{n} + d \times \sum_{\overrightarrow{<q, p> \in E}} \frac{PR(q, t)}{\delta_{out} (q)}$
     19 1. Increment t of one unit
     20 2. Go to step 2 unless reached max number of iterations or
     21     $\sum_{v \in V} PR(v, t) - PR(v, t-1)$
     22 is small enough