SCAM 2009

September 21-25, 2009
University Residential Center
Bertinoro (Forlì-Cesena), Italy

This graduate course will provide a solid introduction to computational advertising (CA), a new scientific discipline, at the intersection of information retrieval, machine learning, optimization, and microeconomics. Its central challenge is to find the best advertisement to present to a user engaged in a given context, such as querying a search engine ("sponsored search"), reading a web page ("content match" and "display ads"), watching a movie on a mobile, or instant messaging and texting. As such, CA provides the foundations for building ad matching platforms that constitute the infrastructure of the $20 billion online advertising industry.

The course will be taught by Andrei Broder, Prabhakar Raghavan and Michael Schwarz.

The course will include three modules: in module 1, we will give an overview of web information retrieval technology with two aims: first, to offer a deeper understanding of web search, one the most important venues for web advertising, and second, to expose the techniques of large scale search that are essential for textual advertising as well. In module 2, we will delve into specific CA technologies: sponsored search, content match, display advertising, mobile advertising, and so on. Finally in module 3 we will discuss the economic aspects of computational advertising.

During the school, several projects for independent research will be discussed. In the past, several projects of this kind have become full-fledged research papers accepted by prestigious venues such as WWW, ACM PODS and others.