8:30-8:40 | Opening Remarks |
8:40-9:40 | Keynote: A Perspective on Targeted Advertising: Principles, Implementation, Controversies |
Andrei Broder | |
9:40-10:20 | Invited talk: Attribution and Marketing Effectiveness in Display Advertising with Unreliable Cookies Using Bayesian Kalman Filtering |
Ram Akella | |
Contributed talk
Learning User Behaviors for Advertisements Click Prediction |
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Invited talk: Story of Phoenix Nest | |
Yang Liu | |
Contributed talk
Effective Blog Advertising by Understanding Bloggerr's Emotions & Needs |
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Contributed talk
Classifying Business Marketing Messages on Facebook |
Accepted Papers
Learning User Behaviors for Advertisements Click PredictionChieh-Jen Wang (National Taiwan University), Hsin-Hsi Chen (National Taiwan University)
Effective Blog Advertising by Understanding Blogger's Emotions & Needs
Yao-sheng Chang (National Cheng Kung Univ.), Wen-hsiang Lu (CSIE, NCKU)
Mobile Advertising: Triple-win for Consumers, Advertisers and Telecom Carrier
Chia-Hui Chang (National Central University), Kuan-Hua Huo (National Central University)
Optimizing Display Advertisements Based on Historic User Trails
Neha Gupta (UMD), Udayan Khurana (UMD), Tak Lee (UMD), Sandeep Nawathe (Tumri Inc.)
Ranking of New Sponsored Online Ads Using Semantically Related Historical Ads
Hamed Neshat (Simon Fraser University), Mohamed Hefeeda (Simon Fraser University)
Classifying Business Marketing Messages on Facebook
Bei Yu (Syracuse University), Linchi Kwok (Syracuse University)
Learning to Active Learn with Applications in the Online Advertising Field of Look-Alike Modeling
James Shanahan (Church and Duncan Group Inc.)
Overview
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.