Node2vec
Overview
By invoking the Word2vec algorithm, the Node2vec algorithm maps nodes in the network to the Euclidean space, and uses vectors to represent the node characteristics.
The Node2vec algorithm generates random steps from each node using the rollback parameter P and forward parameter Q. It combines BFS and DFS. The rollback probability is proportional to 1/P, and the forward probability is proportional to 1/Q. Multiple random steps are generated to reflect the network structures.
Application Scenarios
This algorithm applies to scenarios such as node function similarity comparison, structural similarity comparison, and community clustering.
Parameter Description
Parameter |
Mandatory |
Description |
Type |
Value Range |
Default Value |
---|---|---|---|---|---|
P |
No |
Rollback parameter |
Double |
- |
1 |
Q |
No |
Forward parameter |
Double |
- |
1 |
dim |
No |
Mapping dimension |
Int |
1 to 200, including 1 and 200 |
50 |
walkLength |
No |
Random walk length |
Int |
1 to 100, including 1 and 100 |
40 |
walkNumber |
No |
Number of random walk steps of each node. |
Int |
1 to 100, including 1 and 100 |
10 |
iterations |
No |
Number of iterations |
Int |
1 to 100, including 1 and 100 |
10 |
Precautions
None
Example
Set parameters P to 1, Q to 0.3, dim to 3, walkLength to 20, walkNumber to 10, and iterations to 40 to obtain the three-dimensional vector display of each node.
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