Head: Claudio Carpineto
Moreover, the advanced skills mastered in the field of such advanced technologies are allied to the ability to engineer and develop prototypes using these technologies in order to solve complex problems in specific domains. The area has expertise in statistical monitoring design and the execution of socio-economic phenomena, with skills acquired through analyses of the exponential development of ICT services, with particular regard to the effects of disruptive technologies such as 5G, AI and distributed ledger (blockchain).
We can deal with a range of data types, from structured to semi-structured and unstructured data. Examples include relational records, web pages, spatio-temporal data, tweets, text documents, and multimedia. To extract information from raw data, we employ various data analysis techniques, such as automatic classification, clustering, frequent itemset mining, anomaly detection, web mining, document indexing and ranking, text mining and named-entity recognition, topic modeling and sentiment analysis. These methodologies, together with our own core platform for distributed computing, are currently being employed to solve some challenging issues of public interest, in collaboration with our institutional partners or in synergy with other FUB areas. The problems addressed include: combatting online counterfeiting, preventing corruption in public procurement, monitoring the electromagnetic field, detecting malware, protecting web and data privacy, assessing the socio-economic impact of 5G.
Furthermore, in keeping with our strong record and commitment to research, we continue to investigate scientific issues and conduct editorial activities in the data analytics field.