The group addresses a range of fundamental problems related to information overload and choice complexity which are experienced by individual users and groups while accessing novel, networked, and social information system. Recommender systems and intelligent advisory systems (e.g. Siri, Cortana, Google Now) are becoming ubiquitous applications supporting human computer interaction in several fields. Most of the information that we consume nowadays is generated by filtering algorithms that identify what images, movies, news we will be able to read.
Group members develop techniques and applications that leverage data analysis and prediction models to guide and support users’ decision making and information search processes in diverse domains, such as, e-commerce, e-tourism and cultural heritage. The group also addresses the conceptual underpinnings of the information access and filtering field like, evaluation and optimization methods and mechanisms to address the needs of various groups of users.
The methods and techniques developed by the group have been already applied in several systems in the area of e-tourism, media and health. In these sectors, there is a great demand for personalised decision support systems and in techniques for the analysis of their big data repositories.