TY  - CONF
ID  - www2009127
UR  - http://www2009.eprints.org/127/
A1  - Chang, William
A1  - Pantel, Patrick
A1  - Popescu, Ana-Maria
A1  - Gabrilovich, Evgeniy
Y1  - 2009/04//
N2  - In online advertising, pervasive in commercial search engines, advertisers typically bid on few terms, and the scarcity of data makes ad matching difficult. Suggesting additional bidterms can signi?cantly improve ad clickability and conversion rates. In this paper, we present a large-scale bidterm suggestion system that models an advertiser?s intent and ?nds new bidterms consistent with that intent. Preliminary experiments show that our system signi?cantly increases the coverage of a state of the art production system used at Yahoo while maintaining comparable precision. 
TI  - Towards Intent-Driven Bidterm Suggestion
SP  - 1093
M2  - Madrid, Spain
AV  - public
EP  - 1093
T2  - 18th International World Wide Web Conference
ER  -