In the field of graph machine learning, we need some algorithms to vectorize the graph.
For example, random walk algorithm samples the graph and produces a series of walk sequences, which are then embedding vectorized.
It can be used for graph classification, graph prediction and other application scenarios.
The whole process is roughly as follows：
Refer to paper [Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba]
Here are related papers:
DeepWalk: Online Learning of Social Representations
Feature Description (功能描述)
In the field of graph machine learning, we need some algorithms to vectorize the graph. For example, random walk algorithm samples the graph and produces a series of walk sequences, which are then embedding vectorized. It can be used for graph classification, graph prediction and other application scenarios.
The whole process is roughly as follows：
Refer to paper [Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba]
Here are related papers: