Iván Palomares Carrascosa - Recommender Systems for Personalised Decision Support: trends and

September, 10 at 10:00 (MSC)


Recommender Systems (RS) have gained a lot of popularity in the last two decades as an effective information processing and decision support tool to overcome the Information Overload problem in the Internet: they essentially help us making decisions when there is an overwhelming number of available options. They are used not only in e-commerce sites like Amazon, but also in entertainment portals like Spotify and Netflix, social media platforms, and tourism portals. An RS gathers users’ data to build knowledge about their preferences and predict items (products, services, etc.) that the user is likely to be interested in, thereby providing tailored, personalised recommendations. This lecture introduces the field of recommender systems, highlighting the main families of recommendation algorithms and some underlying data science, machine learning and AI approaches. The current trends and applications in RS research are particularly highlighted and discussed.