Content Technologies and Information Management

• Educational Technology
• Game-based Interaction and Technologies
• Collaborative and Social Environments
• Content Technologies and Information Management
• Internet of Things and Energy Efficiency Technologies
• Natural Interaction and Knowledge Management Technologies

The mission of the research program Content Technologies and Information Management (CTIM) is to study and develop technological solutions that will contribute to social, cultural and economic development through the utilization of digital content.

The vision that underpins the activities of the program is to increase the benefits that can be drawn from the huge amount of content in circulation today. Research interests are therefore guided by the following objectives:

• to increase the accessibility of content, through methodologies and tools for content discovery and cataloging, digital preservation and media convergence;
• to make more effective use of content, through careful user experience design and innovative application models;
• to foster economic return, both in terms of rights management and content repurposing.

The considered application scenarios extend well beyond the traditional value chain of digital content, embracing new models characterized by easy and quick content production aimed at a distribution target strongly biased towards social networks.
To meet the challenges and opportunities opened by such scenarios, the activities of the triennium 2016-2018 will be particularly focused on the field of content interpretation, i.e. the development of solutions for attributing a meaning to content in order to extract the required knowledge to make decisions and choices.
In particular, the study and application of algorithms and computer vision techniques will be the common denominator of three important research projects.
The first project (ESSE3) is aimed at developing a cloud platform for cataloging and sharing content, which will be part of a "social digital library" powered by user-generated content.
The second project (DEEP) will use computer vision for identifying and categorizing objects, people and landmarks, with the aim of creating a cloud platform for analysis and prediction fed by real-time data from social networks and sensors (eg. live-cams).
The third project (ICARE2) is focused on the classification of cutaneous images in the scope of applications aimed at personal well-being and pre-diagnostics.
The program is also committed to consolidating the results achieved with the ACTIVE project, in particular by exploring the possibility to re-use in security applications the face recognition platform developed in this project.

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