196
4
archive
disk0/00/00/01/96
2009-04-06 19:14:40
2009-04-07 14:03:15
2009-04-06 19:14:40
conference_item
show
0
-
Parikh
Nish
eBay Research Laboratories
-
Sundaresan
Neel
eBay Research Laboratories
Buzz-Based Recommender System
pub
public
poster
In this paper, we describe a buzz-based recommender system based on a large source of queries in an eCommerce application. The system detects bursts in query trends. These bursts are linked to external entities like news and inventory information to find the queries currently in-demand which we refer to as buzz queries. The system follows the paradigm of limited quantity merchandising, in the sense that on a per-day basis the system shows recommendations around a single buzz query with the intent of increasing user curiosity, and improving activity and stickiness on the site. A semantic neighborhood of the chosen buzz query is selected and appropriate recommendations are made on products that relate to this neighborhood.
2009-04
1231-1231
18th International World Wide Web Conference
Madrid, Spain
April 20th-24th, 2009
conference
TRUE
196
4
196
1
application/pdf
en
public
p1231.pdf
published
p1231.pdf
691747
http://www2009.eprints.org/196/1/p1231.pdf