The objective of the research unit is the development of theory, techniques and systems for extracting and delivering useful knowledge out of large masses of data.
Today, knowledge discovery and data mining is both a technology that blends data analysis methods with sophisticated algorithms for processing large data sets, and an active research field that aims at developing new data analysis methods for novel forms of data. On one side, classification, clustering and pattern discovery tools are now part of mature data analysis and Business Intelligence systems and have been successfully applied to problems in various commercial and scientific domains. On the other side, the increasing heterogeneity and complexity of the new forms of data – such as those arriving from medicine, biology, the Web, the Earth observation systems, the mobility data arriving from wireless networks – call for new forms of patterns and models, together with new algorithms to discover such patterns and models efficiently.
In this context, the mission of the KDD laboratory is to pursue fundamental research, strategic applications and higher education in the areas of:
It was 1999 when we approached data mining research field. Our exploration of the world of Data is still continuing...
Analysis methods and tools to extract knowledge hidden in the data, including frequent patterns, clustering and classification.
Visual representation coupled with advanced analytics to comprehend and understand complex and large data.
Study and design of methods for assessing privacy risks in data analytics.
A combination of analytic, machine learning, data mining and statistical skills as well as experience with algorithms and technological tools.
Acquiring strategies to manage and analyse large data sets and related tools such as MapReduce, Spark, Hive and Pigas well as NoSQL databases.
Identify hidden sub-structures within complex networks and exploit them to bound homophilic behaviors.
Inferring human mobility information from location data sources such as GPS trajectories, mobile phone traces and social media.
Understand hidden features of products and customers studying their position in the network built over the market.
Track, understand and forecast topological perturbations that affect complex networks as time goes by.
Building frameworks to counter the threats of undesirable, unlawful effects of privacy violation, without obstructing the knowledge discovery opportunities.
Understanding the patterns of success in several fields: sports performance, popularity of artistic items, emergence of new technologies.
Developing new methods of performance measurement by taking advantage of the huge growth of data collected during sport events.
Design algorithms for estimating the distribution of a population across different classes, and for tracking the changes in this distribution.
Design and develop useful tools for understanding, monitoring and signaling diffusion phenomena.
Developing of models to predict the well-being of territories based on Big Data on human behavior.
Design algorithms for discovering discrimination in socially sensitive decision data and for enforcing fairness in data mining models.
Extract meaningful knowledge from complex online and offline social contexts.
Correlate multiple data sources to build and thus understand semantic enriched descriptions of real world networked contexts.
Team work is a fundamental part of our activity: we are the first Lab in Italy for EU projects proposals accepted. Here you'll find the current projects of the KDD Lab. You can also browse our Projects Wall.
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Istituto di Scienza e Tecnologie dell’Informazione
Area della Ricerca CNR
via G. Moruzzi 1
56124 Pisa, Italy
Dipartimento di Informatica
Università di Pisa
Largo B. Pontecorvo 3
56127 Pisa, Italy
Phone: +39 050 621 3013
Fax: +39 050 315 2040