The spectrum of research activities in the realm of Security encompasses several areas, which share the adoption of inductive methods for intelligence and text mining. Another area concerns electronic systems for the treatment of geophysics signals for underwater protection, in conjunction with the Defense Geophysics Group.
The research at SEALab on intelligent data gathering aims to apply Computational-Intelligence
models for Text Mining with a particular emphasis on security-related applications.
The basic goal is to explore a huge amount of data and sift the relevant information for data collection and profiling tasks. The involved methods range from Vector Quantization to Support Vector Machines, and mainly require the integration of heterogeneous techniques. From the viewpoint of computational engines, large scale efficient machine-learning-based methods support the analysis activity and are objects of research in their computational aspects that most influence an efficient mining activity.
Main applicative areas include: Text Mining for data analysis in intelligence, Text Mining applications to Curricula Vitae selection for employee recruitment and job market analysis. The developed methods in this research line, aim at aiding the activiy of the data analyist: in particular the goal is better capturing hidden trends and salient features that would have been difficult to be detected by a human-based inspection.
The research at SEALab on the analysis of geophysics signals aims to support intelligent methods for intrusion detection and undersea security methods. This research is performed within the Defense Geophysics Group in conjunction with INGV (La Spezia) and the NATO UnderSea Research Center (NURC).