Presentation for ISR project about Polyvore recommender system

1. Information Search and Retrieval Spring 2010 FUB Outfit recommendation A collaborative fashion recommendation system for e-commerce Maria Nadejde Lamar Payson

2. Characteristics of the Fashion Domain Large feature set Diversity of consumer taste (styles) Importance of user demographics Short product life (trends, campaigns)

3. Polyvore - A social website for Fashion Clothing items Individual clothing items imported from the web by the users Price, and link to original site automatically recorded Item tags are generated by the user

5. Users may add outfits into collections of outfits

6. Items, Outfits, and Collections may all be “liked” by the user

7. So…

8. Outfits: sets of items

9. Collections: sets of sets of itemsNote: Clothing items and outfits have tags, collections do not

12. But…Sparsity Users: 1.2 million Clothing items: >500,000 (a conservative estimate) Outfits: 30,00 outfits created daily The “Top” outfit for April 29th had only 385 “likes”

13. Outfit Recommendation(cont.) Content Based: Collections Collections liked by user Have have members of Outfits liked by user Outfits Similar Outfits members of Members of have members of Clothing items liked by user Clothing items Similar Clothing items Members of have Tag set

14. Outfit Recommendation (cont.) Hypothesis: The large number of different styles creates highly segmented consumer interests. Collaborative filtering is most desirable but may be precluded by sparsity of data Idea 1: Use the hierarchical structure of data on Polyvore (and collaborative-via-content?) to overcome data sparsity Idea 2: If needed, switch to a cascade method using content based filtering and demographic information (group membership?)