Page Rank — hanaml.PageRank • hana.ml.r

hanaml.PageRank is an R wrapper for SAP HANA PAL page rank algorithm.

hanaml.PageRank(
  data,
  used.cols = NULL,
  damping = NULL,
  max.iter = NULL,
  tol = NULL
)

Arguments

data	`DataFrame` DataFrame containing links among all nodes in a social network.
used.cols	`list of characters, optional` This parameter specifies the two columns for source and sink nodes of all those links in `data`. In the settings here, source node named "source" and sink node named "sink". Defaults to the 1st and 2nd column of `data` if not provided.
damping	`double, optional` The damping factor for PageRank scores. Defautls to 0.85.
max.iter	`integer, optional` The maximum number of iterations of power method for solving the PageRank problem. The value 0 means no maximum number of iterations is set, and the calculation stops when the result converges. Defaults to 0.
tol	`double, optional` The stopping criterion for power method. When the mean improvement value of ranks is less than this value, the program stops calculation. Defaults to 1e-6.

Value

DataFrame
The data frame that contains the ranking scores of all nodes in a network.

Details

PageRank is an algorithm used by a search engine to measure the importance of website pages. A website page is considered more important if it receives more links from other websites. PageRank represents the likelihood that a visitor will visit a particular page by randomly clicking of other webpages. Higher rank in PageRank means greater probability of the site being reached.

Examples

Social networks data that contain existing links between nodes:

> data$Collect()
  FROM_NODE TO_NODE
1     Node1   Node2
2     Node1   Node3
3     Node1   Node4
4     Node2   Node3
5     Node2   Node4
6     Node3   Node1
7     Node4   Node1
8     Node4   Node3

Call the function for calculating the ranking scores of all nodes in the network:

> result <- hanaml.PageRank(data = data,
                            used.cols = c(source = "FROM_NODE", sink = "TO_NODE"),
                            damping = 0.85)

Output:

> result$Collect()
   NODE      RANK
1 Node1 0.3681516
2 Node2 0.1418082
3 Node3 0.2879621
4 Node4 0.2020780