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  1. Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising (ADKDD '07)
  2. A noisy-channel approach to contextual advertising
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Pay-per-action model for online advertising
More bang for their bucks: assessing new features for online advertisers
The economics of attention: maximizing user value in information-rich environments
A noisy-channel approach to contextual advertising
Sensitive webpage classification for content advertising
Sentiment classification with interpolated information diffusion kernels
Extracting opinion topics for Chinese opinions using dependence grammar
Discovering information diffusion paths from blogosphere for online advertising
Finding keyword from online broadcasting content for targeted advertising
From TV to online advertising: recent experience from the Spanish media

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A noisy-channel approach to contextual advertising

Content Provider ACM Digital Library
Author Ciaramita, Massimiliano Murdock, Vanessa Plachouras, Vassilis
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.
Starting Page 21
Ending Page 27
Page Count 7
File Format PDF
ISBN 9781595938336
DOI 10.1145/1348599.1348603
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2007-08-12
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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