Weighted PageRank
The only difference between weighted PageRank and standard PageRank is that edges have weights, and the influence that a vertex receives from an inneighbor is multiplied by the weight of the inedge.
Specifications
tg_pagerank_wt (SET<STRING> v_type_set, SET<STRING> e_type_set, STRING weight_attribute,
FLOAT max_change=0.001, INT maximum_iteration=25, FLOAT damping=0.85, INT top_k=100,
BOOL print_results = TRUE, STRING result_attribute = "", STRING file_path = "",
BOOL display_edges = FALSE)
Parameters
Parameter  Description  Default 


Names of vertex types to use 
(empty string) 

Names of edge types to use 
(empty string) 

Name of edge weight attribute 
(empty string) 

PageRank will stop iterating when the largest
difference between any vertex’s current score and its previous score ≤

0.001 

Maximum number of iterations. 
25 

Fraction of score that is due to the score of neighbors. The balance (1  damping) is a minimum baseline score that every vertex receives. 
0.85 

Sort the scores highest first and output only this many scores 
100 

If True, output JSON to standard output 
True 

If not empty, store PageRank values in FLOAT format to this vertex attribute 
(empty string) 

If not empty, write output to this file. 
(empty string) 

If true, include the graph’s edges in the JSON output, so that the full graph can be displayed. 
False 
Output
Computes a weighted PageRank value (FLOAT type) for each vertex.
The result size is equal to \$V\$, the number of vertices in the graph, because a value is computed for every vertex.