Behavioural analysis and personalization

Online behavior covers a wide spectrum of activities including browsing content, playing games, interacting with web mediated services such as search engines and e-commerce sites, clicking on ads, social media updates, buying physical products and digital goods, etc., etc. Terabytes of data are gathered daily about these online activities but deriving actionable knowledge from them remains a considerable challenge.

The potential benefits are enormous leading simultaneously to better user experiences and to direct economic benefits for advertisers and merchandisers.

There is a need to understand the user behavior both in aggregate (thus enabling e.g. better collaborative filtering and recommendations) and in particular (thus enabling e.g. better personalization and targeting). To this end, we need novel methods that draw from a wide range of fields including machine learning, statistics, algorithms, collaborative filtering, data mining, information retrieval, and user modeling. At the same time we need to take into account the necessary user privacy protections and the practical efficiency of analytical methods. Thus we have a wide field ready for new practical and theoretical research.

For the WWW 2012 behavioral analysis and personalization track, we invite original, high-quality submissions addressing all the aspects of the analysis and use of online behavior. Relevant topics include, but are not restricted to :

Program committee :