TDT4215 - Recommender Systems


Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
work 25/100
Written examination 75/100 4 hours D

Course content

Knowledge management in web-based applications. Semantic Web and ontologies. Open linked data for sharing and collaboration. Linguistic and statistical techniques for text mining and content analysis. Semantic recommender systems.

Learning outcome

Kunnskaper: Basic techniques and semantic languages for engineering ontologies and open linked data. RDF(S) and OWL. SPARQL query language. POS/NER tagging, sentiment analysis and other content analysis techniques. Content-based recommender systems.

Skills: Ability to use semantic technologies and open linked data to analyze unstructured web content and build semantic recommender systems and other intelligent solutions. Ability to define ontologies that may be extended and reused by other peoples' applications.

General competence: Students will learn how semantics and open data are used to extract, represent and provide knowledge on the web, as well as how they can be used in intelligent applications.

Learning methods and activities

Lectures and exercises. The course may be taught in English if taken by students without Norwegian language skills.

Further on evaluation

Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written test (75%) and exercises (25%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. The text for the written final exam will be in English. The candidates may choose to write their answers in either English or Norwegian.
If there is a re-sit examination, the examination form may change from written to oral.
In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken.

Course materials

Announced at start of semester.

Credit reductions

Course code Reduction From To
TDT4215 3.7 01.09.2011
TDT4215 3.7 01.09.2011
More on the course

Version: 3
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2021

No.of lecture hours: 3
Lab hours: 2
No.of specialization hours: 7

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Informatics
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science



Examination arrangement: Portfolio assessment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Spring ORD work 25/100
Room Building Number of candidates
Spring ORD Written examination 75/100 D
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU