This project accompanies our paper published at SPLC 2023, which explores how feature models can be integrated into constraint-based recommender systems.
The core contribution is a set of runtime analysis operations that go beyond static feature model analysis — designed to work in dynamic, real-world recommendation contexts. We demonstrate the approach with a concrete case study in the digital camera recommendation domain.
The work was carried out during my time as a student researcher at Universidad de Sevilla under Prof. David Benavides Cuevas.
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