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. Solutions are analysed from both technological and fundamental perspective. Thus, 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.
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. 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. The research and the applications developed by this group have already received a large recognition in industry and in the academia. Leading publications in this area have been co-authored by group members ("Recommender Systems Handbook", Springer, and the textbook "Recommender Systems An Introduction", CUP).
Francesco Ricci is a full professor at the Faculty of Computer Science of the Free University of Bozen-Bolzano. Find out more about him checking out his website.
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