Prioritization Techniques in Recommender Systems: Application and Evaluation in Kairos
Organisatsiooni nimi
Software Engineering and Information Systems
Kokkuvõte
Recommender systems are pivotal in various domains, providing personalized suggestions to users based on historical data and user preferences. However, the challenge lies in effectively prioritizing these recommendations to enhance user satisfaction and engagement. This thesis project aims to explore and evaluate different prioritization techniques within the context of recommender systems, specifically focusing on their application to the Kairos platform (a prescriptive process mining tool)
The project will begin by researching existing prioritization methods used in recommender systems across various industries. A selection of these techniques will be identified for further exploration and application. The primary objective is to implement these prioritization strategies within Kairos, a platform that requires sophisticated recommendation capabilities to improve user experience.
The evaluation phase will consist of a study to assess the impact of the implemented prioritization methods on the performance and accuracy of recommendations in Kairos.
The project will begin by researching existing prioritization methods used in recommender systems across various industries. A selection of these techniques will be identified for further exploration and application. The primary objective is to implement these prioritization strategies within Kairos, a platform that requires sophisticated recommendation capabilities to improve user experience.
The evaluation phase will consist of a study to assess the impact of the implemented prioritization methods on the performance and accuracy of recommendations in Kairos.
Lõputöö kaitsmise aasta
2024-2025
Juhendaja
Fredrik Milani & Kateryna Kubrak
Suhtlemiskeel(ed)
inglise keel
Nõuded kandideerijale
Tase
Magister
Märksõnad
Kandideerimise kontakt
Nimi
Fredrik Milani
Tel
E-mail