Course - Recommender Systems - TDT4215
TDT4215 - Recommender Systems
About
Examination arrangement
Examination arrangement: School exam
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 4 hours |
Course content
Content based and collaborative filtering methods. Hybrid and context-aware recommender systems. Similarity and prediction functions. Evaluation methods of recommender systems. Semantic Web and ontologies. Open linked data for sharing and collaboration. Linguistic and statistical techniques for text mining and content analysis. Semantic recommender systems. Ethical aspects of recommender systems.
Learning outcome
Content based and collaborative filtering methods. Hybrid and context-aware recommender systems. Evaluation methods of recommender systems. Ethical aspects of recommender systems. Basic techniques and semantic languages for engineering ontologies and open linked data. POS/NER tagging, sentiment analysis and other content analysis techniques. Skills: Ability to pre-process/analyze unstructured web content, build a recommender system and evaluate the system. General competence: Students will learn how recommender systems work, how to use different methods to build and evaluate recommender systems, as well as how to analyse and use unstructured content in recommender systems.
Learning methods and activities
Lectures, exercises and group project. The course is taught in English.
Compulsory assignments
- Group work
Further on evaluation
The final grade in the course is based on written exam 100%. Students must pass from the obligatory group project to be able to take the exam. 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.
Specific conditions
Compulsory activities from previous semester may be approved by the department.
Recommended previous knowledge
Course TDT4145 Data modelling and database systems, or equivalent.
Basic knowledge of machine learning.
Course materials
Announced at start of semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| TDT4215 | 3.7 | AUTUMN 2011 | |
| TDT4215 | 3.7 | AUTUMN 2011 |
Version: 3
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: SPRING 2023
Language of instruction: English
Location: Trondheim
- Informatics
- Technological subjects
Department with academic responsibility
Department of Computer Science
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Spring ORD School exam 100/100 2023-05-12 09:00 INSPERA
-
Room Building Number of candidates - Summer UTS School exam 100/100 INSPERA
-
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"