Advertising is a multi-billion dollar industry that has become a significant component of the Web browsing experience. Online advertising systems incorporate many information retrieval techniques by combining content analysis, user interaction models, and commercial constraints. Advances in online advertising have come from integrating several core research areas: information retrieval, data mining, machine learning, and user modeling.

The workshop will cover a range of topics on advertising, with a focus on application of information retrieval techniques.

The topics will include:

• Similarities and differences between search and advertising systems
• Measuring ad text and landing page appeal
• Commercial intent estimation for search queries
• Ad matching algorithms
• Personalized and customized advertising
• Automatic ad generation
• Local and mobile advertising
• Preserving user, advertiser, and publisher privacy
• Web content analysis for ad selection (keyword extraction, categorization, etc.)
• Detection of aggregators and ‘spam’ advertisers
• Advertising in faceted search and category-based ads
• Geo-targeting and location aware information retrieval
• User centered and user behavioral targeting
• Ads as information supply
• Machine learning for ad selection and ranking
• Ad evaluation techniques and measures