Introduction to Recommender Systems

Recommender systems (RSs) are computer-based techniques that attempt to present information about products that are likely to be of interest to a user. These techniques are mainly used in Electronic Commerce (eCommerce) in order to provide suggestions on items that a customer is, presumably, going to like. Nevertheless, there are other applications that make use of RSs, such as social networks and community-building processes, among others. A recommender system is a specific type of information filtering technique that tries to present users with information about items (movies, music, books, news, web pages, among others) in which they are interested. The term “item” is used to denote what the system recommends to users. To achieve this goal, the user profile is contrasted with the characteristics of the items. These features may come from the item content (content-based approach) or the user’s social environment (CF). The use of these systems is becoming increasingly popular in the Internet because they are very useful to evaluate and filter the vast amount of information available on the Web in order to assist users in their search processes and retrieval. RSs have been highly used and play an important role in different Internet sites that offer products and services in social networks, such as Amazon, YouTube, Netflix, Yahoo!, TripAdvisor, Facebook, and Twitter, among others. Many different companies are developing RSs techniques as an added value to the services they provide to their subscribers.

Details

Code 53084
63084
Type Course
ECTS 5
Site Fribourg
Track(s) T5 – Information Systems and Decision Support
T6 – Data Science
Semester S2020

Teaching

Learning Outcomes
  • To understand the basic concepts of RSs
  • Using a taxonomy, students will be able to classify different RSs solutions
  • To understand a number of RSs algorithms
  • To learn about the different evaluation methods for RSs
Lecturer(s) Luis Terán
Language english
Course Page

The course page in ILIAS can be found at .

Schedules and Rooms

Period Weekly
Schedule Thursday, 10:15 - 13:00
Location UniFR, PER21
Room D230

Additional information

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First Lecture
The first lecture will be announced later.