Problem:

What & Where to eat?

Mei Gao

http://imfeelinghungryy.com/

Topic0

japanese

Topic1

mexican

Topic2

brunchTopic3

bar/atmosphere

Topic4

pizza

Topic 5

compliment

sushi tacos breakfast great pizza great

roll mexican coffee beer crust best

pita salsa eggs happyhour wings love

tuna burrito bacon bar thin good

salmon chips pancakes drinks pepperoni like

Topic6

indian

Topic7

asian

Topic8

fastfood

Topic9

sweets

Topic10

bbq

Topic 11

service(bad)

indian thai burger bagels cheese service

buffet pho fries cheese bbq didn’t

masala chinese potato best sauce never

naan soup onion rings smoothies chicken even

bianco curry dog Iove ribs back

LDA (Latent Dirichlet Allocation) 12 topics

Good restaurant: average star>3.5 Bad restaurant: average star<=3.5

Classification : Weight for each topic

Classifier Linear SVM Logistic

Regression

Random Forest

Accuracy in

Cross Validation 73.67% 81.19% 77.7%

Very Deep learning for image ranking

Training

Evaluation of Recommendation Error Using

Normalized Distance-based Performance Measure (NDPM)

R_2

R_5

R_1

R_3

R_4

R_1

R_2

R_3

R_4

R_5

Recom Actual Ranking

(ground truth)

Minimize NDPM score

Goal:

Mei Gao

Very Deep learning for image ranking

Food Images

Training

Application

Deep hierarchical abstraction Learning structure of images

Deep learning for image ranking

Assessment of LDA

BOW (Bag of Words) LDA

Feature

Dimension 10000 words in dictionary 15 topics

>99%

dimension

reduction

Computation

Efficiency 2.5 hrs 15 min

>90%

computation

time

(2000 samples)

(10 fold cross validation)

Topic0 Topic1 Topic2 Topic3 Topic4

Japanese Mexican brunchBar/

pizzaAtmosphere

sushi tacos breakfast great pizza

roll mexican coffee beer crust

pita salsa eggs happyhour wings

tuna burrito bacon bar thin

salmon chips pancakes drinks pepperoni

Topic5 Topic6 Topic7 Topic8 Topic9

Indian Asian fastfood sweets bbq

Indian Thai burger bagels cheese

buffet Pho fries cheese bbq

masala Chinese potato best sauce

naan soup Onion ring smoothies chicken

bianco curry dog Iove ribs

LDA (Latent DiriChlet Allocation) 15 topics

Topic 10: Compliment

Great, best, live, good, like

Topic 11: Service ( Bad)

Service, didn’t, never, even, back

Assessment of LDA

Dimension Reduction: 99% reduction in dimension

BOW (bag of words) features: 10,000 LDA features: 15 Topics

Computation efficiency: 2000 samples, 10 fold cross validation

BOW features: 2.5 hrs LDA features: 15 min

3%4%

10%

4%

5%

29%

20%

6%

3%

16%

Percentage

others Japanese Mexican Brunch

bar Service compliment Asian

fastfood bbq

Evaluation of Recommendation Error Using

Normalized Distance-based Performance Measure (NDPM)

Rank by recommendation

Rank by user's actual ratings

Restaurant_1 Restaurant_1

Restaurant_2 Restaurant_3

Restaurant_3 Restaurant_7

Restaurant_4 Restaurant_2

Restaurant_5 Restaurant_4

Restaurant_6 Restaurant_9

Restaurant_7 Restaurant_8

Restaurant_8 Restaurant_5

Restaurant_9 Restaurant_10

Restaurant_10 Restaurant_6