Algorithmic Content Exposure

2022/2023

Recommended prerequisite for participation in the module

The course builds on knowledge obtained in the modules “Internet technologies and service architectures” and “Machine Learning”.

Content, progress and pedagogy of the module

Learning objectives

Knowledge

  • Must have knowledge of principles for algorithmic selection of content, e.g. as used in recommender systems
  • Must have knowledge of the key standards of media formats and representation of digital
  • content
  • Must have knowledge of standards for metadata and annotation
  • Must have knowledge of methods for dealing with Digital Rights Management (DRM)
  • Must have knowledge of methods for indexing and handling of unstructured content, e.g.
  • user generated content, in combination with structured media content
  • Must be able to understand how to manage and optimise content adaptation and delivery to meet the limitations of various types of networks and terminals and dynamic context

Skills

  • Must be able to discuss strategies for algorithmically managed exposure of digital content
  • Must be able to prepare and integrate multimedia content in a service, including associated metadata
  • Must be able to analyse the role and interests of content producers, aggregators and providers in the value chain or value network of a service
  • Must be able to analyse problems and solutions for the distribution of digital media content and select appropriate strategies for media distribution

Competences

  • Must have the competency to analyse and evaluate systems and solutions for algorithmically managed exposure of content, e.g. recommender systems
  • Must have the competency to advice content providers and non-technical persons on systems for algorithmic management of content.
  • Must have the competency to analyse technical aspects of content and media management in a larger political-social-economical context

Type of instruction

Types of instruction are listed in § 17.

Exam

Exams

Name of examAlgorithmic Content Exposure
Type of exam
Written or oral exam
ECTS5
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleAlgoritmisk eksponering af indhold
Module codeESNICTEK3K6N
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Copenhagen
Responsible for the module

Organisation

Study BoardStudy Board of Electronics and IT
DepartmentDepartment of Electronic Systems
FacultyThe Technical Faculty of IT and Design