Versatile Graph Embedding from Similarity Measures

1. VERSE
~Versatile Graph Embeddings from Similarity Measures ~
WWW 2018
Anton Tsitsulin, Davide Mottin, Panagiotis Karras and Emmanuel Müller
M1

2. 1.
2.
3.
4.
5.

3. 1.

4. SNS
→
Etc.
(embedding)

5. Network Embedding
( )
Verse Network Embedding

6. “ ”
→ 3 2

7. “ ”
→More Versatile Similarity Notion
More Versatile Similarity Notion
Personalized Pagerank, SimRank,
adjacency similarity

9. →
d: emdedding , m: , n:
t: iteration , s:

10. 2.

11. Network Embedding
embedding
embedding
embedding
3

12. (SVD, t-SNE)
HOPE(2016)
(SVD)
But

13. Random walk
Deep Walk(204)
word2vec skipgram
node2vec(2016)
Deep Walk
→
But

14. SDNE(2016)
embedding
But
CNN
global

15. VERSE
Local : (E,V) matrix
Scalable: 106 1
Nonlinear:
Global:
Versatile :

16. 3.

17. VERSE
( ) G simG(∈N N )
( ) Embedding W(∈N d ) N(0,d-1)
( ) W simE (∈N N)
( ) simG simE KL-divergence
( ) (3),(4)
(4) KL-divergence
Noise Constractive Estimation(NCE).

18. G (simG)
Personalized Pagerank
Adjacency Similarity
SimRank

19. Personalized Pagerank
s
α
πs: A :
v πs simG(v, )

20. W
Embedding u(Wu), v(Wv)
Wu Wv
T
Softmax u
exp(%& ' %()
∑+,-
.
exp(%& ' %+)
simE(v, )

21. KL-divergence
“ ”
Embedding KL-divergence
→ embedding
simG
→L

22. 4.

23. Graph reconstruction
VERSE PPR
Embedding d 128
10

24. 1 0
50%

25. 1% ~ 9%
Macro-F1

26. Kmeans++
K 2~50 k
Modularity

27. Graph reconstruction
Embedding
Cosine

29. – -
CoAuther
VK
Hadamard
Node2vec

30. - -
→ VERSE Node2vec

31. VERSE Louvain

32. Graph reconstruction
VERSE
HS VERSE

33. 5.

34. embedding
→