CS MSc Thesis Zoom Presentation 17 January 2022
Plats: In Zoom: https://lu-se.zoom.us/j/64264975706?pwd=N0VFOWZ1NmFRNTJoQ05JZlFXL293QT09
Kontakt: birger [dot] swahn [at] cs [dot] lth [dot] se
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One Computer Science MSc thesis to be presented on 17 January
Monday, 17 January there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.
The presentation will take place in Zoom (N.B. update): https://lu-se.zoom.us/j/64264975706?pwd=N0VFOWZ1NmFRNTJoQ05JZlFXL293QT09
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Presenter: Astrid Ekman
Title: Designing and implementing a recommender system for an E-learning platform
Examiner: Elin Anna Topp
Supervisors: Rasmus Ros (LTH), Rickard Nygren (Grade AB)
Today many web based companies rely on recommender systems, as these systems may enhance the user experience by presenting only relevant products. In this master thesis a recommender system is designed and implemented based on data given by the E-learning company Grade AB.. The system combines collaborative filtering with demographic filtering by first categorizing the users with k-means clustering and then running matrix factorization on each cluster. The data used for training is historical user-course interactions, meaning that there is a lack of negative feedback.. This may affect the model, why methods that deal with this are presented in the report. Furthermore, since there is one unique model for each of Grade AB's clients, this master thesis also investigates how sensitive the client specific models are for hyper parameters. Additionally, offline evaluation is performed on the models and the constraints of this evaluation technique are discussed.
Link to popular science summary: TBU