Recommender Systems: Methods and Applications
The repetition of the exam will take place on 24.07.15 at 10:30 a.m.
|Vorlesung(V) - Lecture - Dates/Times/Location:|
|Tue.||15:00 bis 17:00||weekly||G22A-113 (24 Pl./11 Pl.CoV19)||Spiliopoulou||20|
|Übung (Ü) - Exercise - Dates/Times/Location:|
|Wed.||11:00 bis 13:00||weekly||G22A-218 (40 Pl./16 Pl.CoV19)||Matuszyk
Overview (from LSF)
In this course we elaborate on the role of recommenders as a primary means of improving a user's or customer's experience, while increasing company revenue. The course covers learning methods for the recommender core, approaches for the design and evaluation of recommenders, and specific application areas of recommenders.
Recommender design and evaluation
Background in data mining is of advantage. This course is also appropriate for students who have heard the CRM/RecSys bachelor course.
|Description||Recommender Systems: Methods and Applications|
- Slides 1a - Setting the scene
- Slides 1b - Design (updated 27.10.14)
- Slides 2a
- Slides 3 - Evaluation
- Slides 4 - Stream Recommenders (updated 29.01.15)
- Exercise sheet 1
- Exercise sheet 2
- Exercise sheet 3
- Exercise sheet 4
- Exercise sheet 5
- Exercise sheet 6
- Exercise sheet 7
Selected exercise slides: