creators_name: Parikh, Nish
creators_name: Sundaresan, Neel
type: conference_item
datestamp: 2009-04-06 19:14:40
lastmod: 2009-04-07 14:03:15
metadata_visibility: show
title: Buzz-Based Recommender System
ispublished: pub
full_text_status: public
pres_type: poster
abstract: 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.
date: 2009-04
pagerange: 1231-1231
event_title: 18th International World Wide Web Conference
event_location: Madrid, Spain
event_dates: April 20th-24th, 2009
event_type: conference
refereed: TRUE
citation: Parikh, Nish <http://www2009.eprints.org/view/author/Parikh=3ANish=3A=3A.html> and Sundaresan, Neel <http://www2009.eprints.org/view/author/Sundaresan=3ANeel=3A=3A.html> (2009) Buzz-Based Recommender System. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain.
document_url: http://www2009.eprints.org/196/1/p1231.pdf