This document discusses using topic modeling techniques like Non-negative Matrix Factorization (NMF) and Latent Dirichlet Allocation (LDA) to analyze a corpus of 2,000 documents about Seattle in order to discover common topics that could be used to recommend potential hosts to visitors. The analysis identified 12 topics in the documents, including "artsy", "yoga", "hippies", "outdoorsy", and "young professional". The document compares the topics discovered using NMF versus LDA.

1. Finding new friends
A different kind of recommendation system

2. https://upload.wikimedia.org/wikipedia/commons/thumb/6/69/Airbnb_Logo_B%C3%A9lo.svg/2000px-Airbnb_Logo_B%C3%A9lo.svg.png
http://images.reserve123.com/images/Seattle-City-Mt-Rainier.jpg

3. What are Seattle hosts like?

8. Sounds like topic modeling.

9. Non-negative Matrix Factorization

10. V = W x H
Non-negative Matrix Factorization

11. V = W x H

12. V = W x HWord-document
matrix

13. V = W x HWord-document
matrix
Word-feature
matrix

14. V = W x HWord-document
matrix
Feature-document
matrix
Word-feature
matrix

15. ≅
Word-document
matrix
Feature-document
matrix
Word-feature
matrix
x

16. Latent Dirichlet Allocation

17. Latent Dirichlet Allocation
corpus

18. Latent Dirichlet Allocation
corpus
w
d

19. document
Latent Dirichlet Allocation
corpus
w
d

20. document
Latent Dirichlet Allocation
corpus
w
d d

21. document
Latent Dirichlet Allocation
corpus
word
w
d d

22. document
Latent Dirichlet Allocation
w
corpus
word
w
d d

23. document
Latent Dirichlet Allocation
w
corpus
word
w
d d w

24. Deterministic
NMF
Stochastic
LDA

25. What is
NMF
What might be
LDA

26. The specifics.

27. 2,000 documents, lemmatized

28. 2,000 documents, lemmatized
Unigrams

29. 2,000 documents, lemmatized
Unigrams
Bigrams

30. 2,000 documents, lemmatized
Unigrams
Bigrams
At least 3 documents

31. 2,000 documents, lemmatized
Unigrams
Bigrams
+ At least 3 documents

32. 2,000 documents, lemmatized
Unigrams
Bigrams
+ At least 3 documents
4,300 unique tokens

33. 12 topics*

34. 12 topics*
*Some assembly required

35. food
music
art
dance
wine
yoga
NMF LDA

36. artsy
NMF LDA

37. yoga
artist
practice
cup
respectful
earth
mother
NMF LDA

38. hippies
NMF LDA

39. anywhere
found
locate
bar
restaurant
bustle
NMF LDA

40. ?
NMF LDA

41. Outdoorsy
NMF LDA
Outdoorsy

42. hike
bike
art
play
music
ski
camp
NMF LDA
hike
outdoors
ski
bike
sport
camp
run

43. hike
bike
art
play
music
ski
camp
NMF LDA
hike
outdoors
ski
bike
sport
camp
run

44. NMF
LDA

45. NMF
LDA
hike
hike

46. NMF
LDA
outdoors
art

47. Professional
NMF LDA
Professional

48. young professional
northwest
business
trail
beauty
Puget Sound
NMF LDA
young professional
business
meeting
company
working
technology

49. young professional
northwest
business
trail
beauty
Puget Sound
NMF LDA
young professional
business
meeting
company
working
technology

50. NMF
LDA

51. NMF
LDA
young
young
professional
professional

52. NMF
LDA
business
northwest

53. Let’s find a host.