Course - Recommender Systems - TDT4215
TDT4215 - Recommender Systems
About
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.
Recommended previous knowledge
Course TDT4145 Data modelling and database systems, or equivalent.
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 |
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
- Informatics
- Technological subjects
Department with academic responsibility
Department of Computer Science
Phone:
Examination
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"