Node2Vec
Node2Vec is a node embedding algorithm that uses random walks in the graph to create a vector representation of a node.
A random walk starts with a node, and the algorithm iteratively selects neighboring nodes to visit, and each neighboring node has an assigned probability. This transforms graph structure into a collection of linear sequences of nodes. For each node we will be left with a list of other nodes from their local or extended neighborhoods.
Once the above step is complete, the algorithm uses a variation of the word2vec model from the language modeling community to turn each node into a vector of probabilities. The probabilities represent the likelihood of visiting a given node in a random walk from each starting node.
Specification
Installing this query requires installing a UDF, which can be found in the Github repository of the query. If you are running the query on a cluster, you need to manually install the UDF on every node of the cluster.
Parameters
Parameter | Description | Data type |
| Number of random walks per node |
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| Number of hops per walk |
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| File path to output results to |
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| Edge types to traverse |
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| Number of nodes to be used in the random sample |
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