This module introduces the main methods of analysis and mining of opinions and personal evaluations for users based on Big Data generated on the web or other sources. Emphasis will be put on text mining method applied to text originated on social media. Lessons will be supported by case studies developed in the SoBigData.eu lab.
The module provides the description of a search engine structure and of Text Mining tools, by analyzing their characteristics and limits with respect to the computational cost, the precision/recall/F1 parameters, and the expressivity of the supported queries. The module is also based on hands-on activities that will present well-known open-source Python tools for the crawling and analysis of web pages, the semantic annotation of texts (TagMe), and the indexing of text data collections (ElasticSearch).
The course will first introduce the fundamentals of artificial neural networks and, then, it will provide an overview of the main techniques and models of the deep learning field. Specific focus will be placed on detailing neural models that are useful for addressing predictive tasks on vectorial, sequential and image data, and to generative deep learning, including variational and adversarial learning.
This module presentes techniques and methods for acquisition of Big Data from a large sources of data available, including mobile phone data, GPS data, customer purchase data, social network data, open and administrative data, environmental and personal sensor data. We discuss also several participatory methods for crowdsourcing or crowdsensing collection of data through ad hoc campains like serious games and viral diffusion.
The module aims to introduce ethical and legal notions of privacy, anonymity, transparency and non-discrimination, also referring the Directives and Regulations of the European Union and their ongoing evolution. The module will show technologies for Privacy-by-Design, for predictive model auditing and for protecting the users' rights and that allow the analysis of Big Data without harming the right to the protection of personal data, to transparency and to a fair treatment.
As graduate researcher at the university of Pisa, Roberto worked initially on algorithms for similarity measures and classification on knowledge graphs (Google Research Award), and later on algorithms for economic networks. He then moved into industry: in Spaziodati he works both on the development of semantic annotation engines and on data science/machine learning projects applied to large economic and textual datasets. In SpazioDati he is also in charge of the SmartDataLake EU project.
Nicola Del Sarto is a post-doctoral research fellow at Scuola Superiore Sant'Anna in Pisa. He received a Ph.D in Management from Scuola Superiore Sant'Anna in 2019. Nicola's research interests focus on start-ups and support mechanisms such as incubators, accelerators and corporate accelerator programs. Moreover, he is investigating the processes of business creation under the Open Innovation paradigm. Nicola holds a Master degree in economics from University of Pisa and a post graduate master in Management, innovation and engineering of services from Scuola Superiore Sant'Anna.
Valentina Cucino is a Postdoctoral Scholar at Scuola Superiore Sant’Anna, Pisa. She received her PhD in Management Innovation, Sustainability and Healthcare from Scuola Superiore Sant’Anna in 2019. Her research interest deals with technology transfer, new business venturing and human resource management.
Postdoctoral Research Fellow at the High Performance Computing Lab at the ISTI-CNR. PhD in Computer Science at the Federal University of Pernambuco, with joint supervision by the University of Pisa. Current research topics include machine learning techniques applied to mobility data for the development of Smart Mobility applications. He has actively collaborated in several Research European Projects involving different areas of Computer Science such as Data Mining, Distributed Computing, and Cloud Computing.
Anna Monreale is an Associate Professor at the Computer Science Department of the University of Pisa and a member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. She has been a visiting student at Department of Computer Science of the Stevens Institute of Technology (Hoboken, NewJersey, USA) (2010).
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