I was born in Pisa, I studied Communication Design at Politecnico (Milano) and in Toronto, Canada. In my Master's thesis, developed inside the DensityDesign research lab, I explored user-generated data visualizations on Wikipedia. I briefly worked in Hamburg as a data visualization designer.
This course aims at teaching the basic theoretical concepts behind the MapReduce distributed computing paradigm, and Hadoop in particular, and at building expertise in the practical usage of high-performance computing tools for data engineering, analysis and mining. In particular, the students will learn how classical data mining algorithms can be applied to Big Data using Hadoop (Spark). Real (and open source) datasets will be used to present examples and to let the students build their own projects.
Claudio Gennaro is a researcher at CNR-ISTI. He received a degree in Electronic Engineering from the University of Pisa in 1994 and a Master in Information Technology from CEFRIEL in Milan. He obtained his Ph.D. in Computer and Automatic Engineering in 1999 at the Politecnico di Milano. His main interests are artificial intelligence, deep learning, access structures for multimedia document retrieval, wireless sensor networks, peer-to-peer systems, digital libraries, performance evaluation, and parallel computing. He authored over 100 papers in international journals and conferences.
Fabrizio Falchi is a researcher of the Artificial Intelligence for Multimedia Information Retrieval group of the Networked Multimedia Information Systems lab of ISTI-CNR He has a Ph.D. in Information Engineering from University of Pisa (Italy), and a Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic). He also received an M.B.A. from Scuola Superiore Sant'Anna in Pisa.
Giuseppe Amato obtained his PhD in Computer Science at the University of Dortmund, Germany, in 2002. He is a senior researcher at CNR-ISTI, where he is leads the research group 'Artificial Inttelligence and Multimedia Information Retrieval' (AIMIR - http://aimir.isti.cnr.it/). His main research interests are Artificial Intelligence, content-based research of multimedia documents, large scale similarity search, intelligent camera networks.
Davide Bacciu is Associate Professor at the Computer Science Department, University of Pisa.
Previously, he was a research associate at the Advanced Robotics Technology and System Laboratory (ARTS Lab), Scuola Superiore Sant’Anna Pisa (2004-2005), and at the Neural Computation Research Group, LJMU (2007-2008). In 2012 he visited the Cognitive Robotic Systems laboratory, Orebro Universitet.
The information circulating on the web and social networks is increasingly multimedia in nature. The possibility to understand the content and to search for multimedia documents on a large scale, expecially in the absence of textual descriptions, has become a strategic tool. The module aims to present tools for analyzing and extracting information from multimedia data, in order to search them in huge databases. This module is based on hands-on work.
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.
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 purpose of the course is to introduce the main techniques in data mining and machine learning (including deep learning approaches) for the analysis of temporal data, in particular for time series and spatio-temporal data related to human mobility. The presentation will be supported by several case studies developed with the SoBigData.eu Laboratory.
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |