July 28, 2011

SIGIR 2011 Workshop: Internet Advertising (IA2011)

Internet advertising, a form of advertising that utilizes the Internet and World Wide Web to deliver marketing messages and attract customers, has seen exponential growth since its inception over 15 years ago, resulting in a $65 billion market worldwide in 2008; it has been pivotal to the success of the World Wide Web.

The dramatic growth of internet advertising poses great challenges to the information retrieval community and calls for new technologies to be developed. Internet advertising is a complex problem. It has different formats, including search advertising, display advertising, social network advertising, in app/game advertising). It contains multiple parties (i.e., advertisers, users, publishers, and ad platforms such as ad exchanges), which interact with each other harmoniously but exhibit a conflict of interest when it comes to risk and revenue objectives. It is highly dynamic in terms of the rapid change of user information needs, non-stationary bids of advertisers, and the frequent modifications of ads campaigns. It is very large scale, with billions of keywords, tens of millions of ads, billions of users, millions of advertisers where events such as clicks and actions can be extremely rare. In addition, the field lies at intersection of information retrieval, machine learning, economics, optimization, distributed systems and information science all very advanced and complex fields in their own right.

For such a complex problem, conventional technologies and evaluation methodologies are not be sufficient, and the development of new algorithms and theories is sorely needed.

The goal of this workshop is to overview the state of the art in Internet advertising, and to discuss future directions and challenges in research and development. We expect the workshop to help develop a community of researchers who are interested in this area, and yield future collaboration and exchanges.

Possible topics include:

IR and advertising

  • CTR prediction
  • Relevancy studies for advertising
  • Behavior targeting and audience selection
  • Ad selection and ranking
  • Ad taxonomy construction and alignment
  • Ad classification and clustering

Evaluation and benchmarks

  • Human labeling for ads
  • Evaluation metrics for ad effectiveness
  • Public benchmarks for academic research
  • Experimental design (considering second order effects)

Beyond traditional advertising

  • In game advertising
  • In app advertising
  • Mobile advertising
  • Social advertising
  • Advertising on four screens
  • Ad Exchanges and RTB: expressing constraints and forecasting Others

Others

  • Credit assignment
  • Privacy protection
  • Auction theory
  • Mechanism design
  • Bid and campaign optimization

The above list is not exhaustive, and we welcome submissions on highly related topics too.

 

 

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taoqin AT microsoft DOT com