Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/12jQfPk. Vaclav Petricek digs some of the romantic interactions nuggets hidden in eHarmony's large collection of human relationships.Filmed at qconnewyork.com. Vaclav Petricek is a Principal Data Scientist at Santa Monica-based eHarmony where he is responsible for optimization and machine learning in eHarmony's core matchmaking algorithms. He also runs a series of invited ML talks at eHarmony. He was Visiting Researcher at University College, London where his research spanned recommender systems, social networks, web structure and online auctions.

1. Wednesday, June 12, 13

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4. Data Science of Love
Vaclav Petricek @petricek
Wednesday, June 12, 13

5. The eHarmony Difference › Who we are
~45% Tech
Wednesday, June 12, 13

6. The eHarmony Difference › Who we are
~15% Customer Care
~45% Tech
Wednesday, June 12, 13

7. The eHarmony Difference › Who we are
~15% Customer Care
~45% Tech
~10% Marketing
Wednesday, June 12, 13

8. The eHarmony Difference › Compatibility Matching System®
Wednesday, June 12, 13

9. The eHarmony Difference › Compatibility Matching System®
Compatibility Matching
System®
Wednesday, June 12, 13

10. The eHarmony Difference › Compatibility Matching System®
Compatibility Matching
System®
Compatibility
Matching
1
Wednesday, June 12, 13

11. The eHarmony Difference › Compatibility Matching System®
Compatibility Matching
System®
Compatibility
Matching
1
Affinity
Matching
2
Wednesday, June 12, 13

12. The eHarmony Difference › Compatibility Matching System®
Compatibility Matching
System®
Match
Distribution
3
Compatibility
Matching
1
Affinity
Matching
2
Wednesday, June 12, 13

13. The eHarmony Difference
Wednesday, June 12, 13

14. Affinity
Matching
Match
Distribution
2 3
The eHarmony Difference › Compatibility Matching System®
Compatibility
Matching
1
Wednesday, June 12, 13

15. Affinity
Matching
Match
Distribution
2 3
The eHarmony Difference › Compatibility Matching System®
Compatibility
Matching
1
Wednesday, June 12, 13

16. Wednesday, June 12, 13

17. Wednesday, June 12, 13

18. 150
ques)ons
Wednesday, June 12, 13

19. 150
ques)ons
Personality
Values
A5ributes
Beliefs
Wednesday, June 12, 13

20. Compatibility Matching › Obstreperousness
Wednesday, June 12, 13

21. Compatibility Matching › Romantic
Wednesday, June 12, 13

22. CMP (CMP Makes Pairings)
Wednesday, June 12, 13

23. CMP (CMP Makes Pairings)
Wednesday, June 12, 13

24. CMP (CMP Makes Pairings)
Wednesday, June 12, 13

25. CMP (CMP Makes Pairings)
Compa)bility
Models
Wednesday, June 12, 13

26. Compatibility Matching ›
Wednesday, June 12, 13

27. Compatibility Matching ›
Wednesday, June 12, 13

28. Match
Distribution
3
Compatibility
Matching
1
Affinity
Matching
2
The eHarmony Difference › Compatibility Matching System®
Wednesday, June 12, 13

29. Match
Distribution
3
Compatibility
Matching
1
Affinity
Matching
2
The eHarmony Difference › Compatibility Matching System®
Layers on Top of
Compatibility Matching
Wednesday, June 12, 13

30. Affinity Matching ›
Wednesday, June 12, 13

31. 61 21
Affinity Matching ›
Wednesday, June 12, 13

32. 61 21
3000
Affinity Matching ›
Wednesday, June 12, 13

33. 61 21
3000
Affinity Matching ›
Wednesday, June 12, 13

34. Affinity Matching ›
Wednesday, June 12, 13

35. ………
Affinity Matching ›
Wednesday, June 12, 13

36. Affinity Matching › Distance
Prob(
)
Wednesday, June 12, 13

37. Affinity Matching › Distance
Wednesday, June 12, 13

38. Affinity Matching › Height difference
Prob(
) 4
-­‐
8
in
cm
Wednesday, June 12, 13

39. Affinity Matching › “Attractiveness”
Prob(
)
Wednesday, June 12, 13

40. Affinity Matching › Zoom level
Wednesday, June 12, 13

41. Affinity Matching › Zoom level
Wednesday, June 12, 13

42. Affinity Matching › Zoom level
Wednesday, June 12, 13

43. 25% -­‐1%-­‐1% -­‐24% 20% 13%
9% -­‐5%-­‐5% -­‐27% 7% 0%9% -­‐5%-­‐5% -­‐27% 7% 0%
-­‐12% -­‐21%-­‐21% -­‐42% -­‐19% -­‐23%
19% 0%0% -­‐28% 28% 10%
9% -­‐11%-­‐11% -­‐35% 11% 44%
Affinity Matching › Food preference
Wednesday, June 12, 13

44. 25% -­‐1%-­‐1% -­‐24% 20% 13%
9% -­‐5%-­‐5% -­‐27% 7% 0%9% -­‐5%-­‐5% -­‐27% 7% 0%
-­‐12% -­‐21%-­‐21% -­‐42% -­‐19% -­‐23%
19% 0%0% -­‐28% 28% 10%
9% -­‐11%-­‐11% -­‐35% 11% 44%
Affinity Matching › Food preference
Wednesday, June 12, 13

45. Wednesday, June 12, 13

46. Wednesday, June 12, 13

47. Wednesday, June 12, 13

48. Wednesday, June 12, 13

49. Wednesday, June 12, 13

50. Affinity Matching ›
~40M
registered
users
~10^7
matches
per
day
~10^3
a5ributes
...
...
Prob( | data)
?
~10^8
daily
Prob( | features)
Wednesday, June 12, 13

51. Affinity Matching ›
~40M
registered
users
~10^7
matches
per
day
~10^3
a5ributes
...
...
Prob( | data)
?
~10^8
daily
Prob( | features)
Unsupervised
features
(LDA,
classifiers)
Constructed
features
Wednesday, June 12, 13

52. 1TB RAM
Wednesday, June 12, 13

53. Maestro: Data
Protocol
Buffers
distcp
Wednesday, June 12, 13

54. Modeling: Maestro
UserMatchCommunica)on
feature
expansion
Sparse
ML
format
models
Wednesday, June 12, 13

55. Modeling: Model parametrizations
Model
parameters
features
weights
tree
splits
Calibra)on
Spline
DISTANCE:534
Wednesday, June 12, 13

56. Modeling: Model parametrizations
Model
parameters
features
weights
tree
splits
Calibra)on
Spline
DISTANCE:534
DSL
Wednesday, June 12, 13

57. Modeling: Scala DSL
“same_religion”:”${user.profile.religion}=={cand.profile.religion}”
“cmp_drinking”:”cmp(${user.profile.drinking},{cand.profile.drinking})”
<
“strict_distance_u”:”${user.profile.accepted_distance}<={pairing.distance}”
60miles
Wednesday, June 12, 13

58. 750M
Compressed
Protocol
Buffers
Production: Spring Conductor
Map-­‐side
joins
(TB)
Matching
User
Serice
Pairings
Browser
Service
1+G
Compressed
Protocol
Buffers
Scorer
Wednesday, June 12, 13

59. ?
Production: FeatureX (expensive features)
FeatureX
LSH
NLP
Voldemort
backed
Service
Wednesday, June 12, 13

60. Production: User Activity Service
User
Ac)vity
Service
10K
events/s
Matching
User
Service
~5ms
response
?
Event
Listener
Wednesday, June 12, 13

61. eHarmony & OpenSource
github.com/petricek/datatools
github.com/eHarmony/seeking
github.com/eHarmony/hive
springsource.org/spring-­‐data/hadoop
github.com/JohnLangford/vowpal_wabbit
Wednesday, June 12, 13

62. Compatibility
Matching
1
Affinity
Matching
2
Match
Distribution
3
The eHarmony Difference › Compatibility Matching System®
Wednesday, June 12, 13

63. Compatibility
Matching
1
Affinity
Matching
2
Match
Distribution
3
The eHarmony Difference › Compatibility Matching System®
Delivering the right
matches at the right
time to as many people
as possible across the
entire network.
Wednesday, June 12, 13

64. Match Distribution › Graph optimization
Wednesday, June 12, 13

65. Match Distribution › Graph optimization
Wednesday, June 12, 13

66. Match Distribution › Graph optimization
2 2
Wednesday, June 12, 13

67. Match Distribution › Graph optimization
2 21
Wednesday, June 12, 13

68. Match Distribution › Graph optimization
2 21Prob( | data)
Wednesday, June 12, 13

69. Match Distribution › Graph optimization
2 21Prob( | data)
Wednesday, June 12, 13

70. Match Distribution › Graph optimization
2 2Prob( | data)
Wednesday, June 12, 13

71. Match Distribution › Graph optimization
2 2Prob( | data)
Wednesday, June 12, 13

72. Resulting Customer Experience › Guided
Communication
Wednesday, June 12, 13

73. Resulting Customer Experience › Guided
Communication
Wednesday, June 12, 13

74. ? !
Resulting Customer Experience › Guided
Communication
Wednesday, June 12, 13

75. Resulting Customer Experience › Success!
Wednesday, June 12, 13

76. Resulting Customer Experience › Success!
Wednesday, June 12, 13

77. eHarmony Results › The eHarmony Impact
2005
90
eHarmony Members
Married Every Day
Wednesday, June 12, 13

78. eHarmony Results › The eHarmony Impact
2005 2007
236
eHarmony Members
Married Every Day
Wednesday, June 12, 13

79. eHarmony Results › The eHarmony Impact
2005 2007 2009
542
eHarmony Members
Married Every Day
Wednesday, June 12, 13

80. Proceedings of National Academy of Sciences
Wednesday, June 12, 13

81. Press coverage
Wednesday, June 12, 13

82. Since
2005,
about
1/3
of
couples
who
have
married
in
the
US
have
met
online
(35%)
eHarmony Results › The eHarmony Impact
*
according
to
survey
of
couples
married
between
2005-­‐2012
by
Harris
InteracQve
for
eHarmony
Wednesday, June 12, 13

83. Rates of breakup or divorce
0%
2.0%
4.0%
6.0%
8.0%
All Online Offline
*
according
to
survey
of
couples
married
between
2005-­‐2012
by
Harris
InteracQve
for
eHarmony
Wednesday, June 12, 13

84. The
largest
number
of
marriages
surveyed
who
met
via
online
da)ng
had
met
on
eHarmony
(25%)
eHarmony Results › The eHarmony Impact
*
according
to
survey
of
couples
married
between
2005-­‐2012
by
Harris
InteracQve
for
eHarmony
Wednesday, June 12, 13

85. Rates of breakup or divorce
0%
2.0%
4.0%
6.0%
8.0%
eHarmony All Other Online Offline
*
according
to
survey
of
couples
married
between
2005-­‐2012
by
by
Harris
InteracQve
for
eHarmony
Wednesday, June 12, 13

86. Rates of breakup or divorce
0%
2.0%
4.0%
6.0%
8.0%
eHarmony All Other Online Offline
*
according
to
survey
of
couples
married
between
2005-­‐2012
by
by
Harris
InteracQve
for
eHarmony
@petricek
linkedin.com/in/petricek
bit.ly/jobateharmony
Wednesday, June 12, 13

87. Watch the video with slide synchronization on
InfoQ.com!
http://www.infoq.com/presentations/eharmony
-hadoop