Introduction to recommender systems

  • Enseignement

    Détails

    Faculté Faculté des sciences et de médecine
    Domaine Informatique
    Code UE-SIN.08613
    Langues Anglais
    Type d'enseignement Cours
    Cursus Master
    Semestre(s) SP-2021

    Horaires et salles

    Horaire résumé Mardi 14:15 - 17:00, Hebdomadaire, PER 21, salle E230
    Struct. des horaires 3h par semaine durant 14 semaines
    Heures de contact 42

    Enseignement

    Responsables
    Enseignants
    Description

    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.

    Objectifs de formation

    - 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

    Commentaire

    MSc-CS BENEFRI - (Code Ue: 53084 Track: T5, Code Ue: 63084 Track: T6) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.

    Softskills
    Non
    Hors domaine
    Non
    BeNeFri
    Oui
    Mobilité
    Oui
    UniPop
    Non
  • Dates et salles
    Date Heure Type d'enseignement Lieu
    23.02.2021 14:15 - 17:00 Cours PER 21, salle E230
    02.03.2021 14:15 - 17:00 Cours PER 21, salle E230
    09.03.2021 14:15 - 17:00 Cours PER 21, salle E230
    16.03.2021 14:15 - 17:00 Cours PER 21, salle E230
    23.03.2021 14:15 - 17:00 Cours PER 21, salle E230
    30.03.2021 14:15 - 17:00 Cours PER 21, salle E230
    13.04.2021 14:15 - 17:00 Cours PER 21, salle E230
    20.04.2021 14:15 - 17:00 Cours PER 21, salle E230
    27.04.2021 14:15 - 17:00 Cours PER 21, salle E230
    04.05.2021 14:15 - 17:00 Cours PER 21, salle E230
    11.05.2021 14:15 - 17:00 Cours PER 21, salle E230
    18.05.2021 14:15 - 17:00 Cours PER 21, salle E230
    25.05.2021 14:15 - 17:00 Cours PER 21, salle E230
    01.06.2021 14:15 - 17:00 Cours PER 21, salle E230
  • Modalités d'évaluation

    Examen écrit

    Mode d'évaluation Par note
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