Towards Intent-Driven Bidterm Suggestion

Presented at: 18th International World Wide Web Conference (WWW2009)

by William Chang, Patrick Pantel, Ana-Maria Popescu, Evgeniy Gabrilovich


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.

Keywords: Poster Session

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