Towards intent-driven bidterm suggestion

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 significantly improve ad clickability and conversion rates. In this paper, we present a large-scale bidterm suggestion system that models an advertiser's intent and finds new bidterms consistent with that intent. Preliminary experiments show that our system significantly increases the coverage of a state of the art production system used at Yahoo while maintaining comparable precision. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms: Algorithms, Experimentation

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: William Chang, Patrick Pantel, Ana-Maria Popescu, Evgeniy Gabrilovich
• Keywords: Ad Clickability, Data Makes Ad, Internet Technology, Retrieval General Terms, WWW 2009