Objectives and outcomes
Students are encountered with advanced, i.e. latest topics in the field of multimedia systems design, in
order to be able to actively and critically design, maintain and use multimedia systems. They know how
to obtain big data for analytics, how to transform and store them in various forms, and how to perform
advanced statistical and artificial intelligence analyses, either by programming specific solutions, using
libraries of algorithms, or combining different tools.
Lectures
Big multimedia data. Concepts and types of multimedia metadata. Generation, collection and
transformation of big multimedia data. Web crawling and scraping. Application of artificial
intelligence to multimedia systems. Multimedia collective intelligence techniques. Multimedia
content recommendation – collaborative filtering. Multimedia search. Automatic search of photos by
properties. Clustering of multimedia content. Finding independent characteristics. Large text as
multimedia content and large text analytics. Techniques, tools and challenges in the development of
complex multimedia applications. Security and copyright protection in multimedia systems.
Practical classes
Using open platforms Knime and Hadoop. Students are trained to independently analyse
and optimise multimedia systems and content, using the tools and techniques they are familiar with.