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- 736 creator deepak-agarwal.
- 736 creator deepayan-chakrabarti.
- 736 creator vanja-josifovski.
- 736 type InProceedings.
- 736 label "Contextual Advertising by Combining Relevance with Click Feedback".
- 736 sameAs 736.
- 736 abstract "Contextual advertising supports much of the Web's ecosystem today. User experience and revenue (shared by the site publisher ad the ad network) depend on the relevance of the displayed ads to the page content. As with other document retrieval systems, relevance is provided by scoring the match between individual ads (documents) and the content of the page where the ads are shown (query). In this paper we show how this match can be improved significantly by augmenting the ad-page scoring function with extra parameters from a logistic regression model on the words in the pages and ads. A key property of the proposed model is that it can be mapped to standard cosine similarity matching and is suitable for efficient and scalable implementation over inverted indexes. The model parameter values are learnt from logs containing ad impressions and clicks, with shrinkage estimators being used to combat sparsity. To scale our computations to train on an extremely large training corpus consisting of several gigabytes of data, we parallelize our fitting algorithm in a Hadoop framework. Experimental evaluation is provided showing improved click prediction over a holdout set of impression and click events from a large scale real-world ad placement engine. Our best model achieves a 25% lift in precision relative to a traditional information retrieval model which is based on cosine similarity, for recalling 10% of the clicks in our test data.".
- 736 hasAuthorList authorList.
- 736 hasTopic World_Wide_Web.
- 736 isPartOf proceedings.
- 736 keyword "Clickthrough rate".
- 736 keyword "Interaction effects".
- 736 keyword "Modeling".
- 736 title "Contextual Advertising by Combining Relevance with Click Feedback".