【推荐系统】Graph Embedding系列

DeepWalk: Online Learning of Social Representations

  1. 论文地址:https://arxiv.org/pdf/1403.6652.pdf 【KDD 2014】
  2. Github地址:https://github.com/phanein/deepwalk
  3. deepwalk工具:http://www.perozzi.net/projects/deepwalk/
  4. 优秀博文:【Graph Embedding】DeepWalk:算法原理,实现和应用

LINE: Large-scale Information Network Embedding

  1. 论文地址:https://arxiv.org/pdf/1503.03578.pdf 【WWW 2015】
  2. Github地址:https://github.com/tangjianpku/LINE
  3. 优秀博文:https://www.jianshu.com/p/8bb4cd0df840
  4. 优秀博文:【Graph Embedding】LINE:算法原理,实现和应用

node2vec: Scalable Feature Learning for Networks

  1. 论文地址:https://www.kdd.org/kdd2016/papers/files/rfp0218-groverA.pdf 【KDD 2016】
  2. Github地址:https://github.com/aditya-grover/node2vec
  3. node2vec的软件实现:http://snap.stanford.edu/node2vec/
  4. 优秀博文:笔记︱基于网络节点的node2vec、论文、算法python实现
  5. 优秀博文:关于Node2vec算法中Graph Embedding同质性和结构性的进一步探讨
  6. 优秀博文:【Graph Embedding】node2vec:算法原理,实现和应用

Structural Deep Network Embedding

  1. 论文地址:https://www.kdd.org/kdd2016/papers/files/rfp0191-wangAemb.pdf 【KDD 2016】

Billion-scale Commodity Embedding for E-commerce
Recommendation in Alibaba

  1. 论文地址:https://arxiv.org/pdf/1803.02349.pdf 【2018】

Graph Neural Networks:
A Review of Methods and Applications

 

https://github.com/shenweichen/GraphEmbedding

 

 

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