PersonalRank
Overview
PersonalRank is also called Personalized PageRank. It inherits the idea of the classic PageRank algorithm and uses the graph link structure to recursively calculate the importance of each node. However, unlike the PageRank algorithm, to ensure that the access probability of each node in the random walk can reflect user preferences, the PersonalRank algorithm returns each hop to the source node at a (1-alpha) probability during random walk. Therefore, the relevance and importance of network nodes can be calculated based on the source node. (The higher the PersonalRank value, the higher the correlation/importance of the source node.)
Application Scenarios
This algorithm applies to fields such as product, friend, and web page recommendations.
Parameter Description
Parameter |
Mandatory |
Description |
Type |
Value Range |
Default Value |
---|---|---|---|---|---|
source |
Yes |
Node ID |
String |
- |
- |
alpha |
No |
Weight 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 |
1000 |
directed |
No |
Whether an edge is directed |
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 defines the sum and upper limit of absolute values of each vertex in each iteration compared with the last iteration. If the sum is less than the value, the computing is considered to be converged and the algorithm stops.
Precautions
When the convergence is set to a large value, the iteration will stop quickly.
Example
Select the algorithm in the algorithm area of the graph engine editor. For details, see Analyzing Graphs Using Algorithms.
Set source to Lee, alpha to 0.85, convergence to 0.00001, max_iterations to 1000, 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 PersonalRank values. The JSON result is displayed in the query result area.
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