Algorithms for Dummies by Mueller John Paul;Massaron Luca; & Luca Massaron

Author:Mueller, John Paul;Massaron, Luca; & Luca Massaron [Mueller, John Paul & Massaron, Luca]
Language: eng
Format: epub
Publisher: John Wiley & Sons, Incorporated
Published: 2022-04-01T00:00:00+00:00

print('Graph A:', PageRank_teleporting(Graph_A,

rounding=8))

print('Graph B:', PageRank_teleporting(Graph_B,

rounding=8))

print('Graph C:', PageRank_teleporting(Graph_C,

rounding=8))

Graph A: [ 0.15477863 0.15346061 0.22122243 0.15477863

0.15787985 0.15787985]

Warning: G is substochastic

Graph B: [ 0.16502904 0.14922238 0.11627717 0.16502904

0.20222118 0.20222118]

Graph C: [ 0.0598128 0.08523323 0.12286869 0.18996342

0.30623677 0.23588508]

After applying the modifications to a new function, PageRank_teleporting(), you can get similar estimates for the first graph as well as much more realistic (and useful) estimates for both the second and third graphs, without falling into the traps of dead ends or rank sinks. Interestingly, the function is equivalent to the one provided by NetworkX: https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.link_analysis.pagerank_alg.pagerank.html.

nx.pagerank(Graph_A, alpha=0.85)

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