Corso di laurea magistrale in Informatica

Background knowledge on relational and object oriented databases.
Preparatory courses (providing the expected entry skills): Propedeutic: A course introductory to DataBases Recommended: Advanced Database Models and Architectures .

The goals of this course are perfectly aligned with those characterizing the Computer Science program, within the area of System for Information Management.

More specifically, the main goal of this course is to teach how to understand, design, develop and manage complex systems, in which the complexity stems from the nature of data - their size, their heterogeneity and in many case multimedia nature.

 

At the end of the course students will have acquired

KNOWLEDGE AND UNDERSTANDING skills.

In particular, they weill know existing problems (and some corresponding solutions) about storage and retrieving of multimedia information, modeling, indexing and ranked retrieval of multimedia, data.Also, management of complex heterogeneous data.

 

APPLYING KNOWLEDGE AND UNDERSTANDING
This skill is acquired thorough the application to real use cases of thetheorical  techniques and algorithms presented in class.To further enhance this skill we continuously create in links and connections between topics, to highlight hoe solutions natively proposed in some application domain might be tuned and adapted to different use cases.

INDEPENDENT JUDGEMENT
This skill is developed by asking students to autinomously suggest solutions to the problems proposed in the practical exercises proposed in class.The text of the assignments is "underspecified", to encourage students to evaluate and choose, independently, reasonable alternatives to be applied within th specified context.

COMMUNICATION SKILLS

 

Each class starts with the request to a student to sumarize in few sentences  the content of the previous class, thus contributing to the ability of syntetically communicating in rigorous terms scientific contents.

 

 

LEARNING SKILLS

This skill is developed thanks to the continuous stimuli to interactions during classes, and through the assignment of independent study of scientific articles, to be discussed together at after an initial analysis by the students.

 

Introduction to multimedia data: characteristics and properties of multimedia data and of multimedia databases Features selection for multimedia data representation. The vector model for multimedia data representation. Multidimensional indexing. Custering of multimedia data. Efficient multimedia query evaluation strategies. Relevance feedback. Dealing with complex data, such as social networks. 6 out of the 9 credits of the course are associated to the theoretical discussion of the contents, and the remaining 3 credits are associated to activities in which students experimentally (or through the study of assigned scientific papers) learn in deep some of the contents discussed on the course. During the course, a number of seminars are offered by international domain experts from academia, or from industrial research labs from the Torino area.

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The course is tough in presence, with the suopport of teaching material (slides, articles) made available to students on the Moodle page of the course.

The exam is oral. The student is asked  a few general questions , to give the teacher the opportunity to evaluate to which degree the student has indeed metabolized the overal view of  the course, followed bysome questions on some specific topics/models/algorithms covered  in the course.

During the exam the students also present and discuss the outcome of their experimental activities. Those students who chose to study in depth some recent scientific articles instead of implementing software will insted present and discuss the assugned articles.