Imagine a commerce world where thematic and seasonal stores could automatically pop up and then disappear with minimal editorial work. Here we talk about the underlying platform that enables mining large-scale user behavior and query data to set up stores automatically based on themes of interest, and emerging and buzz-creating topics. We will describe the science and tools to build experiences that would drive commerce through custom experience and social media, and help sellers, shoppers, and the enthusiasts.

2. Up

7. eBay Showhouse

10. • 4-6 TB of User Session Data Collected Per Day
• 150+ million sessions
• 10+K event types
• Hundreds of millions of user guids

20. Miami Phoenix Tampa Miami DFW
(Colts/Bears) (Giants/Patriots) (Steelers/Cardinals) (Saints/Colts) (Packers/Steelers)

32. Paris Hilton wii
Temporal Pattern in Dotted line and Optimal State Sequence in Solid line

33. http://www.buzzaday.com

40. Multi-year Query Burst
Bursty Queries
Volume Time-series Detection
Index the queries for periodicity
search
Periodically Bursting Queries Non-periodic , one-off buzz events royal
Superbowl Hannukah wedding justin bieber hair
Cluster co-occurring Bursty queries Auto-detected events Cleaning and
based on other dimensions labeling

41. Valentine Wreath
Back to school
Primitive Valentines
Girls backpack
Valentine Cards
Valentines Day Back To School
alice costume boutique halloween handmade costume teen halloween costumes mummy costume bat
costume viking costume alice in wonderland costumes rainbow brite costume handmade costume pikachu
costume ghost costume dora costume couples costume pocahontas costume mens halloween costume jim
shore halloween angel costume gorilla costume zorro costume couples halloween costumes bear costume
referee costume devil costume jester costume mens pirate costume egyptian costume tinker bell costume leg
avenue costume saloon girl costume longaberger halloween werewolf costume funny costume elmo costume
wizard of oz costume homemade costume couples costumes red riding hood costume halloween animated
halloween costumes women gangster costume pig costume frankenstein costume
Halloween

53. Products/
Products/Categ
Volume/Revenu
eCategories
ories
Sellers
Buyers

55. Buyers outnumber sellers 5:1
Seller-items sold has a power law distribution
Seller-revenue has a power law distribution
Buyer-items bought has a power law distribution
For a sample period over 1 month mean is 3 and median is 1
Buyer-spent money has a power law distribution
For a sample period of 1 month mean is 98$ and median was 45$
Categories browsed - mean 10.5, median 5
~10M new items a day, most items eventually sell, items last from a day to 30 days, most items not
cataloged, some auction-some fixed price