# Grover 2016: node2vec: Scalable Feature Learning for Networks

> Aditya Grover, Jure Leskovec, 2016. 1 records on Mysteries Department cite it. The inductive-methods survey proposes it for finding word classes in the…

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[Sources](https://mysteriesdept.com/sources)[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)Grover 2016

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# node2vec: Scalable Feature Learning for Networks

Aditya Grover, Jure Leskovec, 2016. _Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining_.

node2vec learns a vector for every node of a network from biased random walks, so standard machine learning can be applied to nodes and edges.

**Voynich Manuscript** Articledoi: **[10.1145/2939672.2939754](https://doi.org/10.1145/2939672.2939754)** Checked against the original0

## What it's used for here

The inductive-methods survey proposes it for finding word classes in the manuscript's word-adjacency network.

## Cited by on this site 1 record

[1 methods surveys]

Inductive methods

SRC

## Cite it

```
Grover, A., & Leskovec, J. (2016). node2vec: Scalable Feature Learning for Networks. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. https://doi.org/10.1145/2939672.2939754
```

[Find it at doi.org](https://doi.org/10.1145/2939672.2939754)

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