A noisy-channel approach to contextual advertising

ABSTRACT

Contextual advertising is a growing category of search advertising. It presents a particular challenge to ad placement systems because of the sparseness of the language of advertising. We present a system that is language independent and knowledge free based on SVM ranking. We evaluate it on a large number of advertisements appearing on real Web pages. Our contribution is two new classes of features of similarity between ads and Web pages based on machine translation technologies. We show that our features significantly improve performance over baseline techniques.

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