University of Twente Student Theses
As of Friday, 8 August 2025, the current Student Theses repository is no longer available for thesis uploads. A new Student Theses repository will be available starting Friday, 15 August 2025.
Understanding athletes preferences of sport activities through ranking based news feed recommendation
Perenzoni, Stefano (2022) Understanding athletes preferences of sport activities through ranking based news feed recommendation.
|
PDF
2MB |
| Abstract: | Product personalization is essential to provide users with personalized content and retain them. Recommender systems are algorithms which give suggestions on what the users may find more interesting. In this thesis, we want to implement a recommender system to personalize adidas Runtastic's news feed. Firstly, we analyse the historical data of Runtastic apps to understand the business context and needs. This thesis then proposes an approach to optimize diversity within ranking algorithms which does not rely on a diversification-aware loss function. Instead, we suggest Div-NDCG, a diversity-aware evaluation metric to be used in the model selection process to optimize both NDCG and the diversity metric by selecting the best model and dataset. Experiments are conducted on Runtastic historical data, from which we built multiple different datasets. The datasets are built through the combinations of different feature engineering and labelling techniques. Both heuristic-based and machine-learning models are then trained on tested on the datasets. By comparing their performances, we show that the diversity-aware evaluation metric better helps choose a model and dataset that optimize both metrics. Finally, we propose an architecture to implement the tested models on the currently deployed Runtastic apps to provide product personalization. |
| Item Type: | Essay (Master) |
| Clients: | adidas Runtastic, Linz, Austria |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Programme: | Computer Science MSc (60300) |
| Link to this item: | https://purl.utwente.nl/essays/93669 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page