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Recommender Systems

Today's data-deluge motivates the need for new ways to provide people and organisations with access to the right information in the right time. In short, we need to develop more personalised  forms of information access and discovery that are capable of understanding the needs of individuals and responding to these needs in a more targeted way. Recommender systems represent one approach to developing more personalised information systems that have gained considerable traction online, particularly in an e-commerce context. Today, services like Amazon, iTunes, and Netflix help millions of people find what they are looking for by automatically recommending relevant items from a long tail of almost infinite possibilities.
Within Insight we are focusing on developing the next generation of recommender systems and personalisation technologies. These new techniques will learn about our preferences from a wider range of data sources and us this deeper understanding of our needs to make more relevant recommendations and so inform more effective decision making across a wide range of application domains.