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DeepWalk online learning of social representations.

Project description

Usage

$deepwalk –help

input: adjacency list

1 2 3 4 5 6 7 8 9 11 12 13 14 18 20 22 32

2 1 3 4 8 14 18 20 22 31

3 1 2 4 8 9 10 14 28 29 33

output: representations in skipgram format - first line is header, all other lines are node-id and representation

34 64

1 0.016579 -0.033659 0.342167 -0.046998 …

2 -0.007003 0.265891 -0.351422 0.043923 …

Requirements

  • numpy
  • scipy

(may have to be independently installed)

Installation

  1. cd deepwalk
  2. pip install -r requirements.txt
  3. python setup.py install

Citing

@inproceedings{2014-perozzi-deepwalk,

author = {Bryan Perozzi and Rami Al-Rfou and Steven Skiena},

title = {DeepWalk: Online Learning of Social Representations},

booktitle = {Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},

series = {KDD ‘14},

year = {2014},

month = {August},

location = {New York, NY, USA},

publisher = {ACM},

address = {New York, NY, USA},

}

Misc

DeepWalk - Online learning of social representations.

https://badge.fury.io/py/deepwalk.png https://travis-ci.org/phanein/deepwalk.png?branch=master https://pypip.in/d/deepwalk/badge.png

History

1.0.0 (2014-08-24)

  • First release on PyPI.

Project details


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