2018/11/06

1. 1

2. ■ Matrix Factorization
■ Context-Aware MF
■ Factorization Machines
■ Bayesian Probabilistic Matrix Factorization
■ Bayesian Personalized Ranking
2

3. Matrix Factorization
■ User-item
– user item
■ Matrix Factorization user item
3
×
User-item User Item

4. Matrix Factorization
■ user item
user item
■ SGD
4
×
Vector dimension k

5. Matrix Factorization
■ user item
5
User a
Item 2
Item 3
User
user
Item
item
User d

6. Matrix Factorization
6
User a
Item 2
Item 3
User
Item
user item
User d
user
item
■ user item

7. Matrix Factorization
7
User a
Item 2
Item 3
User
user
User d
User a
Item 2
Item 3
User d
Item
item

8. Matrix Factorization
■
8
• k
•
User :
Item :

9. Matrix Factorization
9
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R
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#%

10. Matrix Factorization
10
U
R
V
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#%
User

11. Matrix Factorization
11
U
R
V
!
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#%
Item

12. Matrix Factorization
12
U
R
V
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#%

13. Matrix Factorization
■
13
SVD

14. Matrix Factorization
■
14
! "
1 0
#$
%&

15. Matrix Factorization
■
15

16. Convolutional Matrix Factorization
for Document Context-Aware
Recommendation
Donghyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, Hwanjo Yu
16
2016, RecSys

17. ConvMF
■ Item
■ Item
17
…

18. ConvMF
18
U
R
V
!
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%
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%
#%
'
X
W
#(
%

19. ConvMF
19
U
R
V
!
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%
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%
#%
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W
#(
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MF CNN

20. ConvMF
20
U
R
V
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W
#(
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CNN

21. ConvMF
21
U
R
V
!
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W
#(
%
Item

22. ConvMF
22
CNN 4
1. Embedding layer
2. Convolution layer
3. Pooling layer
4. Output layer

23. ConvMF
1. Embedding layer
23
Document
!! − 1 ! + 1
n
n Glove
2

24. ConvMF
2. Convolutional layer
24
!
…
Document Matrix
Window size "#
1 1
Contextual feature
$%

25. ConvMF
3. Pooling layer
25
n Contextual feature
n Document
max-pooling

26. ConvMF
4. Output layer
26
User & Item !

27. ConvMF
■
27
SGD + Back-prop

28. ConvMF
■
28
CNN

29. ConvMF
■
29
u
u p PMF :
p CTR : PMF + LDA
p CDL : PMF + SDAE
p ConvMF :
p ConvMF+ : Glove

30. ConvMF
■
30
RMSE

31. ConvMF
■
■
31

32. Factorization Machines
Steffen Rendle
32
2010, IEEE International Conference on Data Mining

33. FMs
■ Matrix Factorization
■ MF User Item
–
33

34. FMs
■
34
1.
User Item Time Rating
2. one-hot encoding
User Item Time Rating

35. FMs
■
35

36. FMs
■
36

37. FMs
■
37
User
Item

38. FMs
■ Alice Titanic 2010 1
38

39. FMs
39
Alice Titanic
2010 1 /

40. FMs
40
Alice Titanic
Alice Titanic
Alice 2010 1
Titanic 2010 1

41. FMs
■
41
! …
" …
"
!

42. FMs
■
– 3
– Ranking Binary Classification
–
Field-Aware Factorization Machines
42
[1]
[1] Field-Aware Factorization Machines for CTR Prediction
Y. Juan, Y. Zhuang, W. -S. Chin, C. -J. Lin
2016, RecSys

43. FMs
■ Domain-specific
– Matrix Factorization / Tensor decomposition
– SVD++
– Pairwise Interaction Tensor Factorization
– Factorized Personalized Markov Chains
or
43

44. Bayesian Probabilistic Matrix
Factorization using
Markov Chain Monte Carlo
Ruslan Salakhutdinov, Andriy Mnih
44
2008, ACM

45. BPMF
■ Matrix Factorization User Item
!"
#
!$
#
■
■
■
–
–
–
45

46. BPMF
46
U
R
V
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(& ('()
*), ,)
*), ,)
()

47. BPMF
47
U
R
V
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(& ('
)*, ,*
)*, ,*
(*
(*
User

48. BPMF
48
U
R
V
!
"
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Λ& Λ'
(& ('
)*, ,*
)*, ,*
(*
(*
User

49. BPMF
■ MCMC Gibbs sampling …
■
■
49

50. BPMF
■
50
u
u
p Netflix baseline : Netflix
p SVD
p PMF
p Logistic PMF : 0~1
p Bayesian PMF :

51. BPMF
■
51

52. BPMF
■
52

53. BPMF
■ User Item
53

54. BPMF
■ User Item
54

55. Bayesian Personalized
Ranking from Implicit
Feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
55
2009, UAI

56. BPR
■ Matrix Factorization
■
■
56

57. BPR
■ BPR
57

58. BPR
■ BPR
58
Θ
" #
$
"
# $

59. BPR
■
59
BPR

60. BPR
■
60

61. BPR
■ MF
61

62. BPR
■ AUC
62
AUC 0.94
0.77
0.49
0.26
1
1
1
0
…
…
1.

63. BPR
■ AUC
63
3. AUC
AUC
2. 1
0

64. BPR
■ AUC
64
AUC
0.94
0.77
0.49
0.26
1
1
1
0
…
…
…
0
1
1→0
0→1

65. BPR
■ AUC
65

66. BPR
■ AUC
66
!
" #
BPR

67. BPR
■
67
u
u
p WR-MF : 1 [0, 1]
p SVD-MF
p Cosine-kNN
p most popular :
p np_max :

68. BPR
■
68
AUC

69. Reference
■
■ Donghyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, Hwanjo Yu.
Convolutional Matrix Factorization for Document Context-Aware
Recommendation, 2016, RecSys
■ Steffen Rendle. Factorization Machines, 2010, IEEE International Conference
on Data Mining
■ Ruslan Salakhutdinov, Andriy Mnih. Bayesian Probabilistic Matrix Factorization
using Markov Chain Monte Carlo, 2008, ACM
■ Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme.
Bayesian Personalized Ranking from Implicit Feedback, 2009, UAI
69