creators_name: Gupta, Manish
type: conference_item
datestamp: 2009-04-06 19:11:48
lastmod: 2009-04-07 14:02:45
metadata_visibility: show
title: Predicting Click Through Rate for Job Listings
ispublished: pub
full_text_status: public
pres_type: poster
abstract: Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher’s revenue, advertiser’s bid amounts in “pay for performance” business models. We learn regression models using features of the job, optional click history of job, features of “related” jobs. We show that our models predict CTR much better than predicting avg. CTR for all job listings, even in absence of the click history for the job listing.
date: 2009-04
pagerange: 1053-1053
event_title: 18th International World Wide Web Conference
event_location: Madrid, Spain
event_dates: April 20th-24th, 2009
event_type: conference
refereed: TRUE
citation: Gupta, Manish <http://www2009.eprints.org/view/author/Gupta=3AManish=3A=3A.html> (2009) Predicting Click Through Rate for Job Listings. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain.
document_url: http://www2009.eprints.org/107/1/p1053.pdf