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 in-neighbor is multiplied by the weight of the in-edge.

Specifications

tg_pageRank_wt (SET<STRING> v_type, SET<STRING> e_type, STRING wt_attr,
  FLOAT max_change=0.001, INT max_iter=25, FLOAT damping=0.85, INT top_k=100,
   BOOL print_accum = TRUE, STRING result_attr =  "", STRING file_path = "",
   BOOL display_edges = FALSE)

Characteristic Value

Characteristic	Value
Result	Computes a weighted PageRank value (FLOAT type) for each vertex.
Input Parameters	`STRING v_type`: Names of vertex type to use `STRING e_type`: Names of edge type to use `STRING wt_attr`: Name of edge weight attribute `FLOAT max_change`: PageRank will stop iterating when the largest difference between any vertex’s current score and its previous score ≤ `max_change`. That is, the scores have become very stable and are changing by less than `max_change` from one iteration to the next. `INT max_iter`: Maximum number of iterations. `FLOAT damping`: Fraction of score that is due to the score of neighbors. The balance (1 - damping) is a minimum baseline score that every vertex receives. `INT top_k`: Sort the scores highest first and output only this many scores `BOOL print_accum`: If True, output JSON to standard output `STRING result_attr`: If not empty, store PageRank values (FLOAT) to this attribute `STRING file_path`: If not empty, write output to this file. `BOOL display_edges`: If true, include the graph’s edges in the JSON output, so that the full graph can be displayed.
Result Size	V = number of vertices
Time Complexity	O(E*k), E = number of edges, k = number of iterations. The number of iterations is data-dependent, but the user can set a maximum. Parallel processing reduces the time needed for computation.
Graph Types	Directed edges

Result

Computes a weighted PageRank value (FLOAT type) for each vertex.

Input Parameters

STRING v_type: Names of vertex type to use
STRING e_type: Names of edge type to use
STRING wt_attr: Name of edge weight attribute
FLOAT max_change: PageRank will stop iterating when the largest difference between any vertex’s current score and its previous score ≤ max_change. That is, the scores have become very stable and are changing by less than max_change from one iteration to the next.
INT max_iter: Maximum number of iterations.
FLOAT damping: Fraction of score that is due to the score of neighbors. The balance (1 - damping) is a minimum baseline score that every vertex receives.
INT top_k: Sort the scores highest first and output only this many scores
BOOL print_accum: If True, output JSON to standard output
STRING result_attr: If not empty, store PageRank values (FLOAT) to this attribute
STRING file_path: If not empty, write output to this file.
BOOL display_edges: If true, include the graph’s edges in the JSON output, so that the full graph can be displayed.

Result Size

V = number of vertices

Time Complexity

O(E*k), E = number of edges, k = number of iterations.

The number of iterations is data-dependent, but the user can set a maximum. Parallel processing reduces the time needed for computation.

Graph Types

Directed edges