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page_rank's Introduction

MN - Google PageRank Algorithm

->This program was implemented in Octave => Install octave

->The first task implements the Iterative version of the algorithm

  • I make the system matrix in a separate matrix in which if there is a link from i to j then we have a link and put 1 in M ​​[i] [j].

  • At the same time I find out the link vector.

  • I find the link matrix M and calculate it according to the formula.

  • Iterations stop when the difference between two Pagerank vectors consecutive is less than the given error

->The second requirement involves the algebraic implementation of the algorithm

  • Same story as above, but you will need to calculate rank knowing that :

     R = (d*M + ( 1 - D)/ nr*E)*R cu E*R= 1, so
     R = (I - d*M)^(-1) * ( 1 - d ) / nr
  • The last relation represents a superior triangular system, which is solved by the SST() method.

For the third requirement

  • I put all the data in the file. :)

  • We sorted the descending vector and looked for the initial position of each element in the sorted vector in the initial one

  • To find the affiliation we applied the function of U(X) and we found the values ​​of the variables a and b according to the known val_1 and val_2.

  • To find the two varaible a si b make a sistem at limit val1 and val2:

    1 = a*val2 + b
    0 = a*val1 + b
    ---------------> substract
    1 = a*(val2 - val1)
    b = a - a * val1

Documentation:

->Feedback

A very interesting topic that made me quite curious about what happens behind a search engine that I use every day.

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