Sciweavers

Share
KDD
2009
ACM

Catching the drift: learning broad matches from clickthrough data

11 years 4 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Effective broad matching leads to improvements in both relevance and monetization, while increasing advertisers' reach and making campaign management easier. In this paper, we present a learning-based approach to broad matching that is based on exploiting implicit feedback in the form of advertisement clickthrough logs. Our method can utilize arbitrary similarity functions by incorporating them as features. We present an online learning algorithm, Amnesiac Averaged Perceptron, that is highly efficient yet able to quickly adjust to the rapidly-changing distributions of bidded keywords, advertisements and user behavior. Experimental results obtained from (1) historical logs and (2) live trials on a large-scale advertising platform demonstrate the effectiveness of the proposed algorithm and the overall success...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
Added 25 Nov 2009
Updated 25 Nov 2009
Type Conference
Year 2009
Where KDD
Authors Sonal Gupta, Mikhail Bilenko, Matthew Richardson
Comments (0)
books