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According to the paper《node2vec: scalable feature learning for networks》.
The current random walk algorithm requires 2 additional features.
Biased random walk.
Second order random walk.
Biased random walk, control the probability of walking edges through edge weight.
Second order random walk, add 2 parameters to control the walking strategy.
(1) parameter p, called return factor. Controls the probability of re-walk to a previously walked vertex
(2) parameter q, called in-out factor. Controls whether to walk inward or outward.
Please refer to the paper design diagram:
P1
P2
The text was updated successfully, but these errors were encountered:
- implement #279
- follow-up #274 (V1 version)
The current random walk algorithm requires 2 additional features.
- Biased random walk.
- Second order random walk.
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Co-authored-by: diaohancai <[email protected]>
Co-authored-by: imbajin <[email protected]>
Feature Description (功能描述)
According to the paper《node2vec: scalable feature learning for networks》.
The current random walk algorithm requires 2 additional features.
Biased random walk, control the probability of walking edges through edge weight.
Second order random walk, add 2 parameters to control the walking strategy.
(1) parameter p, called return factor. Controls the probability of re-walk to a previously walked vertex
(2) parameter q, called in-out factor. Controls whether to walk inward or outward.
Please refer to the paper design diagram:
P1
P2
The text was updated successfully, but these errors were encountered: