PageRank

Overview

PageRank, also known as web page ranking, is a hyperlink analysis algorithm used to rank web pages (nodes) based on their search engine results. PageRank is a way of measuring the relevance and importance of web pages (nodes).

If a web page is linked to many other web pages, the web page is of great importance. That is, the PageRank value is relatively high.
If a web page with a high PageRank value is linked to another web page, the PageRank value of the linked web page increases accordingly.

Application Scenarios

This algorithm applies to scenarios such as web page sorting and key role discovery in social networking.

Parameter Description

**Table 1** PageRank algorithm parameters
Parameter	Mandatory	Description	Type	Value Range	Default Value
alpha	No	Weight coefficient (also called damping coefficient)	Double	A real number between 0 and 1 (excluding 0 and 1)	0.85
convergence	No	Convergence	Double	A real number between 0 and 1 (excluding 0 and 1)	0.00001
max_iterations	No	Maximum iterations	Int	1-2,000	1,000
directed	No	Whether to consider the edge direction	Bool	true or false	true

alpha determines the jump probability coefficient, also called damping coefficient, which is a computing control variable in the algorithm.
convergence indicates the upper limit of the sum of each absolute vertex change between an iteration and the last iteration. If the sum is less than the value of this parameter, the computing is considered converged and the algorithm stops.
When the convergence is set to a large value, the iteration will stop quickly.

Precautions

When the convergence is set to a large value, the iteration will stop quickly.

Example

Set parameters alpha to 0.85, coverage to 0.00001, max_iterations to 1,000, and directed to true. The sub-graph formed by top nodes in the calculation result is displayed on the canvas. The size of a node varies with the PageRank values. The JSON result is displayed in the query result area.