WWW2009 EPrints

A Search-based Method for Forecasting Ad Impression in Contextual Advertising

This item is a Paper in the Search track.

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Contextual advertising (also called content match) refers to the placement of small textual ads within the content of a generic web page. It has become a significant source of revenue for publishers ranging from individual bloggers to major newspapers. At the same time it is an important way for advertisers to reach their intended audience. This reach depends on the total number of exposures of the ad (impressions) and its click-through-rate (CTR) that can be viewed as the probability of an end-user clicking on the ad when shown. These two orthogonal, critical factors are both difficult to estimate and even individually can still be very informative and useful in planning and budgeting advertising campaigns. In this paper, we address the problem of forecasting the number of impressions for new or changed ads in the system. Producing such forecasts, even within large margins of error, is quite challenging: 1) ad selection in contextual advertising is a complicated process based on tens or even hundreds of page and ad features; 2) the publishers’ content and traffic vary over time; and 3) the scale of the problem is daunting: over a course of a week it involves billions of impressions, hundreds of millions of distinct pages, hundreds of millions of ads, and varying bids of other competing advertisers. We tackle these complexities by simulating the presence of a given ad with its associated bid over weeks of historical data. We obtain an impression estimate by counting how many times the ad would have been displayed if it were in the system over that period of time. We estimate this count by an efficient two-level search algorithm over the distinct pages in the data set. Experimental results show that our approach can accurately forecast the expected number of impressions of contextual ads in real time. We also show how this method can be used in tools for bid selection and ad evaluation.

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About this site

This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.

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If you are presenting a paper or poster and have slides or supporting material you would like to have permentently made public at this website, please email cjg@ecs.soton.ac.uk - Include the file(s), a note to say if they are presentations, supporting material or whatnot, and the URL of the paper/poster from this site. eg. http://www2009.eprints.org/128/

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We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it...

Fun Stuff

WWW2009 EPrints supports OAI 2.0 with a base URL of http://www2009.eprints.org/cgi/oai2
The JSON URL is http://www2009.eprints.org/cgi/json?callback=function&eprintid=number

To prevent google killing the server by hammering these tools, the /cgi/ URL's are denied to robots.txt - ask Chris if you want an exception made.

Feel free to contact me (Christopher Gutteridge) with any other queries or suggestions. ...Or if you do something cool with the data which we should link to!

Handy Tools

These are not directly related to the EPrints set up, but may be of use to delegates.

Social tool links
I've put links in the page header to the WWW2009 stuff on flickr, facebook and to a page which will let you watch the #www2009 tag on Twitter. Not really the right place, but not yet made it onto the main conference homepage. Send me any suggestions for new links.
When demoing live websites, use this tool to shorten the current URL and make it appaer real big, your audience can then easily type in the short URL and get to the same page as you. Available as a javascript bookmark