Research Topics in Recommender Systems



Mål og innhald

This course offers an overview of approaches to develop and evaluate state-of-the-art recommender system methods. In particular, this course makes an extensive introduction to current algorithmic approaches for generating personalized recommender approaches, such as collaborative and content-based filtering, as well as more advanced methods such as hybrid recommender approaches, context-aware methods and approaches relying on machine learning techniques. The course will also discuss in detail how to evaluate recommender systems from an algorithmic and an interface perspective and what needs to be considered when adopting standard recommender approaches to particular domains or use cases.


A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The candidate

  • has fundamental knowledge about the central concepts behind recommender systems
  • has broad knowledge about state-of-the-art recommender system algorithms
  • has extensive knowledge about how to efficiently evaluate recommender systems
  • has knowledge about the current research trends in recommender systems


The candidate

  • is able to implement state-of-the-art recommender system algorithms
  • can develop their own recommender system
  • is able to deploy HCI and machine learning routines to evaluate recommender systems
  • is able to teach laymen about how recommender systems work

Studienivå (studiesyklus)

Master level


Krav til forkunnskapar
European (three-year) Bachelor's degree in information science or similar degree in ICT, covering basic programming skills.
Krav til studierett
Master Programme in Information Science. Students admitted to other Master´s programs and international exchange students may also be qualified to apply for the course.
Arbeids- og undervisningsformer
Lectures, and work with assignments, presentations and discussions.
Obligatorisk undervisningsaktivitet
  • Assignments throughout the semester which must be completed and approved.
  • Participation at 80% of course seminars.
  • Compulsory requirements are only valid the semester they are approved.

  • Individual written school exam (30%)
  • Practical group assignment project (70%)
  • Both the exam and the assignment paper must be done in the teaching semester.

    The exam assignment will be given in the language of instruction in the course.
    The exam answer must be submitted in the same language as the exam assignment.

    The grading system has a descending scale from A to E for passes and F for fail.

    Assessment in teaching semester

    Retake exam

    School exam:

    A retake exam is arranged for students with valid absence according to § 5-5. If there is a retake exam, this will be available for students with the follow results/absences:

    • Medical certificate/valid absence
    • Interruption during the exam
    • Fail/failed

    If you have the right to take a retake exam and a retake exam is arranged for students with valid absences, you can sign up yourself in Studentweb after January 15/August 1.

    Group assignment:

    Students with valid absence as defined in the UiB regulations § 5-5 can apply for an extended submission deadline to The application must be submitted before the deadline for submission has expired.

    Alle emne blir evaluert i tråd med UiBs kvalitetssystem for utdanning.