|CREDITS||6 credits during the 2nd year of 11160 COMPUTER ENGINEERING (LM-32) GENOVA|
|SCIENTIFIC DISCIPLINARY SECTOR||ING-INF/05|
|TEACHING LOCATION||GENOVA (COMPUTER ENGINEERING )|
The Semantic Web and Linked Data technologies are the fulcrum of this teaching: starting from XML and RDF up to the conceptual representations in OWL. These technologies, and the associated methodologies, will be used in the design and implementation of "smart" user interfaces, which exploit ontologies and open and linked data.
Finally, software tools and use cases will be presented to compare Semantic Web and Machine Learning in the management of datasets and complex systems.
In this course, you will learn the fundamentals of Semantic Web technologies. You will learn how to collect information form linked data and metadata to represent knowledge an build knowledge bases, and how to access and benefit from semantic web technologies applied to smart applications in a H2020 perspective.
At the end of the course the student will acquire skills and competencies related to design and implementation of “smart” apps and services based on semantic technologies.
Lectures (online and/or face-to-face) and thematic seminars will be provided during the fall semester. Online activities will be delivered through UniGe digital platforms to permit a continuous assessment of students' competencies.
Office hours: In attendance: by appointment via e-mail at the DIBRIS (office S04, Villa Bonino 2nd floor) in Viale Francesco Causa 13, Genoa or at the 3DLabFactory (room T.008, Palazzina Lagorio, ground floor), Campus di Savona, Via A. Magliotto 2, Savona Remote call: by appointment via e-mail at email@example.com During the semester the teacher will be available at the end of the planned activities, always by appointment, except impediments.
GIANNI VIARDO VERCELLI (President)
GIOVANNI ADORNI (President Substitute)
All class schedules are posted on the EasyAcademy portal.
Oral presentation of the assigned final project and evaluation of intermediate online activities.
The exam grading is based on the mean average between scores of continuous evaluation of online activities carried out during the semester (50%) and the oral presentation of the assigned final project on course topics (50%).