Data Analytics Area comprehends projects in information retrieval, data mining and big data, as well as scenario analyses based on data, such as economic and market analyses on ICT development.
Moreover, the advanced skills mastered in the field of such advanced technologies are complemented with the ability to engineer and develop prototypes using these technologies in order to solve complex problems in specific domains. The area has competences on statistical monitoring design and execution of socio-economic fenomena, with skills acquired through analyses of exponential development of ICT services with particular regard to 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 are 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, 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. Problems addressed comprehend: fighting 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 perform editorial activities in the data analytics field.